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Journals

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Conferences

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Books

Patent

Journals

#TitleYear
71Akhtar, M.S., Zafar, Z., Mahmood, Z., Naeem, M.K., Yermekbayev, K. and Fraz, M.M., 2026. Boundary-Consistent Ordinal Regression for wheat yield prediction using UAV-based multispectral time-series data. Computers and Electronics in Agriculture, 246, p.111665. https://doi.org/10.1016/j.compag.2026.1116652026
70Zhang, Y., Sadiq, M., Fraz, M.M., Aldhahri, E.A., Almazroi, A.A., Iqbal, M., Hayat, A., Geng, Y., Algamdi, A.S., Noreen, A. and Fatima, A., 2026. Artificial intelligence and machine learning in optoelectronics and energy storage: From materials design to device applications. Sustainable Materials and Technologies p.e01949. https://doi.org/10.1016/j.susmat.2026.e019492026
69Mansoor, I., Abdullah, M., Rizwan, M.D. and Fraz, M.M., 2026. Reasoning with large language models in medicine: a systematic review of techniques, challenges and clinical integration. Health Information Science and Systems, 14(1), p.6.https://doi.org/10.1007/s13755-025-00403-02026
68Athar, U., Ali, M., Zafar, Z., Mahmood, Z., Berns, K., Bourennani, F. and Fraz, M.M., 2026. Phenology-aware in-season crop yield estimation through UAV multispectral imagery and deep neural networks. Computers and Electronics in Agriculture, 240, p.111210.https://doi.org/10.1016/j.compag.2025.1112102026
67Akhtar, M.S., Zafar, Z., Mahmood, Z., Khurshid, H., Naseem, M.R., Berns, K. and Fraz, M.M., 2025. Advancing Spatiotemporal Orthophoto Registration in UAV-based Crop Breeding Experiments Leveraging Field Geometric Features. PFG–Journal of Photogrammetry, Remote Sensing and Geoinformation Science, pp.1-26.https://doi.org/10.1007/s41064-025-00365-82025
66Umer, M.S., Nabeel, M., Athar, U., Lynch, I., Afantitis, A., Ullah, S. and Fraz, M.M., 2025. Large Language Models Meet Molecules: A Systematic Review of Advances and Challenges in AI-Driven Cheminformatics. Archives of Computational Methods in Engineering, pp.1-42.
https://doi.org/10.1007/s11831-025-10437-y		2025
65Khalid, M.A., Zulfiqar, K., Bashir, U., Shaheen, A., Iqbal, R., Rizwan, Z., Rizwan, G. and Fraz, M.M., 2025. A Benchmark Dataset for Automatic Cephalometric Landmark Detection and CVM Stage Classification. Scientific Data, 12(1), p.1336.https://doi.org/10.1038/s41597-025-05542-32025
64Khurshid, A., Khan, B., Shahzad, M. and Fraz, M.M., 2025. TVFace: towards large-scale unsupervised face recognition in video streams. Pattern Analysis and Applications, 28(2), pp.1-21. https://doi.org/10.1007/s10044-025-01464-32025
63Zouraris, D., Mavrogiorgis, A., Tsoumanis, A., Saarimäki, L.A., del Giudice, G., Federico, A., Serra, A., Greco, D., Rouse, I., Subbotina, J., Lobaskin, V. and Fraz, M.M., 2025. CompSafeNano project: NanoInformatics approaches for safe-by-design nanomaterials. Computational and Structural Biotechnology Journal. https://doi.org/10.1016/j.csbj.2024.12.0242025
62Saadat, A., Faheem, Y., Abaid, Z. and Fraz, M.M., 2024. Cloud security in the age of adaptive adversaries: A game theoretic approach to hypervisor-based intrusion detection. Journal of Systems Architecture, 156, pp.103281. https://doi.org/10.1016/j.sysarc.2024.1032812024
61Parvaiz, A., Nasir, E.S. and Fraz, M. M., 2024. From Pixels to Prognosis: A Survey on AI-Driven Cancer Patient Survival Prediction Using Digital Histology Images. Journal of Imaging Informatics in Medicine, pp.1-24. https://doi.org/10.1007/s10278-024-01049-22024
60Asghar, H.A., Khan, B., Zafar, Z., Sabri, A.Q.M. and Fraz, M.M., 2024. Pakvehicle-reid: a multi-perspective benchmark for vehicle re-identification in unconstrained urban road environment. Multimedia Tools and Applications, 83(17), pp.53009-53024. https://doi.org/10.1007/s11042-023-17070-62024
59Aftab, K., Tschirren, L., Pasini, B., Zeller, P., Khan, B. and Fraz, M.M., 2024. Intelligent Fisheries: Cognitive Solutions for Improving Aquaculture Commercial Efficiency Through Enhanced Biomass Estimation and Early Disease Detection. Cognitive Computation, pp.1-23. https://doi.org/10.1007/s12559-024-10292-22024
58Akhtar, M.S., Zafar, Z., Nawaz, R. and Fraz, M.M., 2024. Unlocking plant secrets: A systematic review of 3D imaging in plant phenotyping techniques. Computers and Electronics in Agriculture, 222, pp.109033. https://doi.org/10.1016/j.compag.2024.1090332024
57Khurshid, M., Shahzad, M., Khattak, H.A., Malik, M.I. and Fraz, M.M., 2024. Vision Based 3D Localization of UAV Using Deep Image Matching. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. https://doi.org/10.1109/JSTARS.2024.34223102024
56Khalid, M.A., Khurshid, A., Zulfiqar, K., Bashir, U. and Fraz, M.M., 2024. A two-stage regression framework for automated cephalometric landmark detection incorporating semantically fused anatomical features and multi-head refinement loss. Expert Systems with Applications, pp.124840. https://doi.org/10.1016/j.eswa.2024.1248402024
55Nasir, E.S., Rasool, S., Nawaz, R. and Fraz, M.M., 2024. AFINITI: attention-aware feature integration for nuclei instance segmentation and type identification. Neural Computing and Applications, pp.1-19. https://doi.org/10.1007/s00521-024-10114-42024
54Khan, M.Q., Shahzad, M., Khan, S.A., Fraz, M.M. and Zhu, X.X., 2024. Beyond local patches: Preserving global–local interactions by enhancing self-attention via 3D point cloud tokenization. Pattern Recognition, 155, pp.110712. https://doi.org/10.1016/j.patcog.2024.1107122024
53Khan, B., Mumtaz, A., Zafar, Z., Sedkey, M., Benkhelifa, E. and Fraz, M. M., 2023. CGA-Net: channel-wise gated attention network for improved super-resolution in remote sensing imagery.. Machine Vision and Applications 34, 6(2023), pp.128. https://doi.org/10.1007/s00138-023-01477-02023
52Nawshad, M. A., Saadat, A. and Fraz, M. M., 2023. Boosting facial recognition capability for faces wearing masks using attention augmented residual model with quadruplet loss.. Machine Vision and Applications 34, 6(2023), pp.108. https://doi.org/10.1007/s00138-023-01461-82023
51Soltani, H., Amroune, M., Bendib, I., Haouam, M. Y., Benkhelifa, E. and Fraz, M. M., 2023. Breast lesions segmentation and classification in a two-stage process based on Mask-RCNN and Transfer Learning.. Multimedia Tools and Applications, pp.1-18. https://doi.org/10.1007/s11042-023-16895-52023
50Parvaiz, A., Khalid, M. A., Zafar, R., Ameer, H., Ali, M. and Fraz, M. M., 2023. Vision Transformers in medical computer vision—A contemplative retrospection. Engineering Applications of Artificial Intelligence, 122, pp.106126. https://doi.org/10.1016/j.engappai.2023.1061262023
49Perwaiz, N., Shahzad, M. and Fraz, M. M., 2023. TransPose Re-ID: transformers for pose invariant person Re-identification.. Journal of Experimental & Theoretical Artificial Intelligence, pp.1-14. https://doi.org/10.1080/0952813X.2023.22145702023
48Zahra, A., Perwaiz, N., Shahzad, M. and Fraz, M. M., 2023. Person re-identification: A retrospective on domain specific open challenges and future trends. Pattern Recognition, 142, pp.109669. https://doi.org/10.1016/j.patcog.2023.1096692023
47Rashid, S. N. and Fraz, M. M., 2023. Nuclei probability and centroid map network for nuclei instance segmentation in histology images.. Neural Computing and Applications, 35(21). https://doi.org/10.1007/s00521-023-08503-22023
46Rizvi, S. K. J. and Fraz, M. M., 2023. Robust malware clustering of windows portable executables using ensemble latent representation and distribution modeling.. Concurrency and Computation: Practice and Experience, 35(8), pp.7621. https://doi.org/10.1002/cpe.76212023
45Perwaiz, N., Shahzad, M. and Fraz, M. M., 2023. Ubiquitous vision of transformers for person re-identification. Machine Vision and Applications, 34, pp.27. https://doi.org/10.1007/s00138-023-01376-42023
44Hassan, R, Fraz, MM, Rajput, A and Shahzad, M, 2023. Residual Learning with Annularly Convolutional Neural Networks for Classification and Segmentation of 3D Point Clouds. Neurocomputing. https://doi.org/10.1016/j.neucom.2023.01.0262023
43Dogar, G. M., Shahzad, M. and Fraz, M. M., 2023. Attention augmented distance regression and classification network for nuclei instance segmentation and type classification in histology images. Biomedical Signal Processing and Control, 79, pp.104199. https://doi.org/10.1016/j.bspc.2022.1041992023
42Nasir, E. S., Parvaiz, A. and Fraz, M. M., 2023. Nuclei and glands instance segmentation in histology images: a narrative review.. Artificial Intelligence Review, 56(8), pp.7909-7964. https://doi.org/10.1007/s10462-022-10372-52023
41Pervaiz, N., Fraz, M. M. and Shahzad, M, 2022. Smart surveillance with simultaneous person detection and re-identification. Multimed Tools Appl. https://doi.org/10.1007/s11042-022-13458-y2022
40Pervaiz, N., Fraz, M. M. and Shahzad, M, 2022. Per-former: rethinking person re-identification using transformer augmented with self-attention and contextual mapping. Vis Comput. https://doi.org/10.1007/s00371-022-02577-02022
39Zaidi, S. S. Ali, Fraz, M. M., Shahzad, M. and Khan, S., 2022. A multiapproach generalized framework for automated solution suggestion of support tickets. International Journal of Intelligent Systems, 37(6), pp.3654-3681. https://doi.org/10.1002/int.227012022
38Badawi, S.A., Fraz, M. M., Shehzad, M. and al, et, 2022. Detection and Grading of Hypertensive Retinopathy Using Vessels Tortuosity and Arteriovenous Ratio. J Digit Imaging, 35, pp.281-301. https://doi.org/10.1007/s10278-021-00545-z2022
37Rizvi, S.K.J., Azad, M.A. and Fraz, M.M., 2021. Spectrum of Advancements and Developments in Multidisciplinary Domains for Generative Adversarial Networks (GANs). Arch Computat Methods Eng, 28, pp.4503-4521. https://doi.org/10.1007/s11831-021-09543-42021
36Rizwi, S. K. J., Aslam, W., Shahzad, M., Saleem, S. and Fraz, M. M., 2021. PROUD-MAL: static analysis-based progressive framework for deep unsupervised malware classification of windows portable executable. Complex & Intelligent Systems, 21(2). https://doi.org/10.1007/s40747-021-00560-12021
35Zaidi, S. S. A., Fraz, M. M. and Shahzad, M, 2021. A multiapproach generalized framework for automated solution suggestion of support tickets. International Journal of Intelligent Systems, 21(2). https://doi.org/10.1002/int.227012021
34Perwaiz​, N., Fraz, M. M. and Shahzad, M, 2021. Stochastic attentions and context learning for person re-identification. PeerJ Computer Science, pp.7. https://doi.org/10.7717/peerj-cs.4472021
33Rizwi, S. K. J., Azad, M. A. and Fraz, M. M., 2021. Spectrum of Advancements and Developments in Multidisciplinary Domains for Generative Adversarial Networks (GANs). Archives of Computational Methods in Engineering, 2021(1). https://doi.org/10.1007/s11831-021-09543-42021
32Khurram, I, Fraz, M.M., Shahzad, M and Rajpoot, NM, 2021. Dense-CaptionNet: A Sentence Generation Architecture for Fine-Grained Description of Image Semantics. Cognitive Computing, 13(1), pp.595-691. https://doi.org/10.1007/s12559-019-09697-12021
31Mahmood, I., Mobeen, M., Rahman, A. U., Younis, S., Malik, A. W., Fraz, M. M. and KafaitUllah, 2020. Modeling, simulation and forecasting of wind power plants using agent-based approach. Journal of Cleaner Production, 276(1). https://doi.org/10.1016/j.jclepro.2020.1241722020
30Mehmood, S., Shahzad, M. and Fraz, M.M., 2020. DCARN: Deep Context Aware Recurrent Neural Network for Semantic Segmentation of Large Scale Unstructured 3D Point Cloud. Neural Processing Letters, 52(3). https://doi.org/10.1007/s11063-020-10368-82020
29Javed, S., Mahmood, A., Fraz, M. M., Koohbanani, NA, Benes, K., Tsang, Y., Hewitt, K., Epstein, D, Snead, D. and Rajpoot, N. M., 2020. Cellular community detection for tissue phenotyping in colorectal cancer histology images. Medical Image Analysis, 63(1). https://doi.org/10.1016/j.media.2020.1016962020
28Hashmi, M.A., Riaz, Q., Shahzad, M.Z.M. and Fraz, M. M., 2020. Motion Reveal Emotions: Identifying Emotions from Human Walk Using Chest Mounted Smartphone. IEEE Sensors Journal, 2020(1). https://doi.org/10.1109/JSEN.2020.30043992020
27Haroon, M., Shahzad, M. and Fraz, M.M., 2020. Multi-sized Object Detection Using Spaceborne Optical Imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS). https://doi.org/10.1109/JSTARS.2020.30003172020
26Shaban, M., Awan, R., Fraz, M.M., Azam, A., Tsang, Y., Snead, D. and Rajpoot, N.M., 2020. Context-Aware Convolutional Neural Network for Grading of Colorectal Cancer Histology Images. IEEE Transactions on Medical Imaging, 21(1). https://doi.org/10.1109/TMI.2020.29710062020
25Zaheer, T., Malik, A. W., Rahman, A. U., Zahir, A. and Fraz, M. M., 2019. A vehicular network–based intelligent transport system for smart cities. International Journal of Distributed Sensor Networks, 10(1). https://doi.org/10.1177/15501477198888452019
24Fraz, M.M., Khurran, S. A., Graham, S., Shaban, M., Loya, Asif and Rajpoot, N. M., 2019. FABnet: Feature attention based network for simultaneous segmentation of microvessels and nerves in routine histology images of oral cancer. Neural Computing and Applications, 20(1). https://doi.org/10.1007/s00521-019-04516-y2019
23Fraz, M.M., Badar, M., Malik, A.W. and Barman, S. A., 2019. Computational Methods for Exudates Detection and Macular Edema Estimation in Retinal Images: A Survey. Archives of Computational Methods in Engineering, 26(4), pp.1193. https://doi.org/10.1007/s11831-018-9281-42019
22Shaban, M., Khurram, S.A., Fraz, M. M., Alsubaie, N., Masood, I., Mushtaq, S., Hassan, M., Loya, A. and Rajpoot, N. M., 2019. A Novel Digital Score for Abundance of Tumour Infiltrating Lymphocytes Predicts Disease Free Survival in Oral Squamous Cell Carcinoma. Nature Scientific Reports, 9(1), pp.13341. https://doi.org/10.1038/s41598-019-49710-z2019
21Ahmed, S. B., Ali, S. F., Ahmad, J., Adnan, M. and Fraz, M. M., 2019. On the Frontiers of Pose Invariant Face Recognition: A Review. Artificial Intelligence Review, 2019(1), pp.1-64. https://doi.org/10.1007/s10462-019-09742-32019
20Arshad, S., Shahzad, M., Riaz, Q. and Fraz, M. M., 2019. DPRNet: Deep 3D Point based Residual Network for Semantic Segmentation and Classification of 3D Point Clouds. IEEE Access, 8(1). https://doi.org/10.1007/s10462-019-09742-32019
19Badawi, S. A. and Fraz, M. M., 2019. Multiloss Function Based Deep Convolutional Neural Network for Segmentation of Retinal Vasculature into Arterioles and Venules. BioMed Research International, 2019(1), pp.17. https://doi.org/10.1155/2019/47472302019
18Bashir, R. M. S., Shahzad, M. and Fraz, M. M., 2019. VR-PROUD: Vehicle Re-identification using PROgressive Unsupervised Deep architecture. Pattern Recognition, 90(1), pp.52-65. https://doi.org/10.1016/j.patcog.2019.01.0082019
17Owen, C. G., Rudnicka, A. R, Welikala, R. A, Fraz, M. M., Barman, S. A, Luben, R., Hayat, S. A, Khaw, K. T., Strachan, D. P, Whincup, P. H and Foster, P. J, 2019. Retinal vasculometry associations with cardiometabolic risk factors in the European Prospective Investigation of Cancer Norfolk study. Ophthalmology, 126(1), pp.96-106. https://doi.org/10.1016/j.ophtha.2018.07.0222019
16Pervaiz, N., Fraz, M. M. and Shahzad, M, 2018. Person Re-Identification Using Hybrid Representation Reinforced by Metric Learning. IEEE Access, 7(1). https://doi.org/10.1109/ACCESS.2018.28822542018
15Badawi, S.A. and Fraz, M.M., 2018. Optimizing the trainable B-COSFIRE filter for retinal blood vessel segmentation. PeerJ, 6(1), pp.5855. https://doi.org/10.7717/peerj.58552018
14Zahoor, M. N. and Fraz, M. M., 2018. A Correction to the Article “Fast Optic Disc Segmentation in Retina Using Polar Transform”. IEEE Access, 6(1), pp.4845. https://doi.org/10.1109/ACCESS.2018.27900402018
13Fraz, M. M, Jahangir, W., Zahid, S., Hamayun, M. M. and Barman, S. A., 2017. Multiscale segmentation of exudates in retinal images using contextual cues and ensemble classification. Biomedical Signal Processing and Control, 35(1), pp.50-62. https://doi.org/10.1016/j.bspc.2017.02.0122017
12Abdullah, M., Fraz, M.M. and Barman, S.A., 2016. Localization and segmentation of optic disc in retinal images using Circular Hough transform and Grow Cut algorithm. PeerJ, 4(1), pp.1-23. https://doi.org/10.7717/peerj.20032016
11Welikala, RA, Fraz, M.M., Foster, PJ, Whincup, PH, Rudnicka, AR, Owen, CG, Strachan, DP and Barman, SA, 2016. Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies. Computers in Biology and Medicine, 71(1), pp.67. https://doi.org/10.1016/j.compbiomed.2016.01.0272016
10Fraz, M.M., Welikala, R.A., Rudnicka, A.R., Owen, C.G., Strachan, D.P. and Barman, S.A., 2015. QUARTZ: Quantitative Analysis of Retinal Vessel Topology and size – An automated system for quantification of retinal vessels morphology. Expert Systems with Applications, 42(20), pp.7221. https://doi.org/10.1016/j.eswa.2015.05.0222015
9Welikala, R.A., Fraz, M.M., Williamson, T.H. and Barman, S.A., 2015. The automated detection of proliferative diabetic retinopathy using dual ensemble classification. International Journal of Diagnostic Imaging, 2(2), pp.72. https://doi.org/10.5430/ijdi.v2n2p722015
8Welikala, R.A., Fraz, M.M., Dehmeshki, J., Hoppe, A., Tah, V., Mann, S., Williamson, T.H. and Barman, S.A., 2015. Genetic algorithm based feature selection combined with dual classification for the automated detection of proliferative diabetic retinopathy. Computerized Medical Imaging and Graphics, 43(7), pp.64-77. https://doi.org/10.1016/j.compmedimag.2015.03.0032015
7Basit, A. and M.M.Fraz, 2015. Optic disc detection and boundary extraction in retinal images. Applied Optics, 54(11), pp.3440-3447. https://doi.org/10.1364/AO.54.0034402015
6Fraz, M.M., Rudnicka, A.R., Owen, C.G. and Barman, S.A., 2014. Delineation of blood vessels in paediatric retinal images using decision trees-based ensemble classification. International journal of computer assisted radiology and surgery, 9(5), pp.795-811. https://doi.org/10.1007/s11548-013-0965-92014
5Fraz, M.M., Basit, A. and Barman, S.A., 2013. Application of Morphological Bit Planes in Retinal Blood Vessel Extraction. Journal of Digital Imaging, 26(2), pp.274-286. https://doi.org/10.1007/s10278-012-9513-32013
4Fraz, M.M., Remagnino, P., Hoppe, A., Rudnicka, A., Owen, C.G., Whincup, P.H. and Barman, S.A., 2013. Quantification of blood vessel calibre in retinal images of multi-ethnic school children using model based approach. Computerized Medical Imaging and Graphics, 37(1), pp.48-60. https://doi.org/10.1016/j.compmedimag.2013.01.0042013
3Fraz, M.M., Barman, S.A., Remagnino, P., Hoppe, A., Basit, A., Uyyanonvara, B., Rudnicka, A.R. and Owen, C.G., 2012. An approach to localize the retinal blood vessels using bit planes and centerline detection. Computer Methods and Programs in Biomedicine, 108(2), pp.600-616. https://doi.org/10.1016/j.cmpb.2011.08.0092012
2Fraz, M.M., Remagnino, P., Hoppe, A., Uyyanonvara, B., Rudnicka, A.R., Owen, C.G. and Barman, S.A., 2012. Blood vessel segmentation methodologies in retinal images – A survey. Computer Methods and Programs in Biomedicine, 108(1), pp.407-433. https://doi.org/10.1016/j.cmpb.2012.03.0092012
1Fraz, M.M., Remagnino, P., Hoppe, A., Uyyanonvara, B., Rudnicka, A.R., Owen, C.G. and Barman, S.A., 2012. An Ensemble Classification-Based Approach Applied to Retinal Blood Vessel Segmentation. IEEE Transactions on Biomedical Engineering, 59(9), pp.2538-2548. https://doi.org/10.1109/TBME.2012.22056872012

Conferences

#TitleYear
101Kashif, F., Sultan, A., Rizwan, M.D., Bajwa, M.N., Shahzad, M.W. and Fraz, M.M., 2026, May. From Segmentation to Structured Reports: Auditable Continual Learning for Automation in Medical Imaging Diagnostics. In 2026 International Conference on Robotics and Automation in Industry (ICRAI) (pp. 1-6). IEEE. https://doi.org/10.1109/ICRAI70912.2026.115519282026
100Nabeel, M., Khan, A., Rizwan, M.D., Malik, M.I. and Fraz, M.M., 2026, May. HunarmandAI: A Bilingual Intelligent Diagnostic Interface for Smart Vehicles and Industrial Mechatronic Systems. In 2026 International Conference on Robotics and Automation in Industry (ICRAI) (pp. 1-6). IEEE. https://doi.org/10.1109/ICRAI70912.2026.115519442026
99Riaz, H., Haroon, A., Baig, M., Rizwan, M.D., Bajwa, M.N. and Fraz, M.M., 2026, May. XMedFusion: A Knowledge-Guided Multimodal Perception and Reasoning Framework for Autonomous Medical Systems. In 2026 International Conference on Robotics and Automation in Industry (ICRAI) (pp. 1-6). IEEE. https://doi.org/10.1109/ICRAI70912.2026.115519562026
98Iftikhar, M.T., Imran, A., Umar, M.H., Athar, U., Zafar, Z., Fraz, M.M., Akhtar, M.S., Mahmood, Z., Naeem, M.K. and Khurshid, H., 2026, May. Analyzing UAV-Based Multispectral Data for Genotypic-Aware Crop Performance Assessment. In 2026 International Conference on Robotics and Automation in Industry (ICRAI) (pp. 1-6). IEEE. https://doi.org/10.1109/ICRAI70912.2026.115519432026
97Sultan, S., Ullah, M.S., Jan, A., Rizwan, M.D., Bajwa, M.N. and Fraz, M.M., 2026, May. MedLingo: Resource-Efficient Hierarchical Multi-Agent Intelligence for Autonomous Clinical and Robotic Diagnostics. In 2026 International Conference on Robotics and Automation in Industry (ICRAI) (pp. 1-6). IEEE. https://doi.org/10.1109/ICRAI70912.2026.115519632026
96Shehzadi, A., Fraz, M.M., Ali, S.I., Bilal, H.S.M. and Satti, F.A., 2026, April. A Hybrid Multimodal Architecture for Named Entity Recognition on Social Media Using Domain-Specific Language Modelling and Token-Level Gated Visual Fusion. In 2026 39th Conference of Open Innovations Association (FRUCT) (pp. 271-280). IEEE.https://doi.org/10.23919/FRUCT70069.2026.115065602026
95Rizwan, M.D., Khan, N.A., Zafar, Z., Berns, K. and Fraz, M.M., 2025, December. Bridging Performance and Efficiency: Distilling Vision Transformers for Remote Sensing. In 2025 5th International Conference on Digital Futures and Transformative Technologies (ICoDT2) (pp. 1-6). IEEE..https://doi.org/10.1016/j.susmat.2026.e019492025
94Abdullah, M., Mansoor, I., Rey, V.F. and Fraz, M.M., 2025, December. A Multi-LLM Pipeline for Retrieval-Grounded, Bloom’s Taxonomy-Aligned Question Generation. In 2025 5th International Conference on Digital Futures and Transformative Technologies (ICoDT2) (pp. 1-6). IEEE.https://doi.org/10.1109/ICoDT269104.2025.113607482025
93Amjad, M.S., Ghaffar, M.J., Athar, U. and Fraz, M.M., 2025, December. Pixel-Based Glacial Change Monitoring Across Hindu Kush, Karakoram, & Himalayan Ranges. In 2025 International Conference on Frontiers of Information Technology (FIT) (pp. 1-6). IEEE. https://doi.org/10.1109/FIT67061.2025.113336362025
92Fatima, S.Z., Raees, M., Athar, U., Asif, M.D.A., Zafar, Z., Khurshid, H., Berns, K. and Fraz, M.M., 2025, November. Semi-Supervised Contrastive Representation Learning for Sunflower Phenology Estimation. In 2025 20th International Conference on Emerging Technologies (ICET) (pp. 1-7). IEEE. https://doi.org/10.1109/ICET66147.2025.113214332025
91Ali, M., Athar, U., Zafar, Z., Khattak, H.A., Berns, K. and Fraz, M.M., 2025, August. Combining UAV Multispectral Data & Crop Morphological Features for Sunflower Oil Content Estimation. In IGARSS 2025-2025 IEEE International Geoscience and Remote Sensing Symposium (pp. 2973-2977). IEEE. https://doi.org/10.1109/IGARSS55030.2025.112430002025
90Khan, M.S., Ahmed, F., Wahab, A., Zafar, Z., Berns, K. and Fraz, M.M., 2025, October. AgriFormer: Advancing 3D LiDAR-based Biomass Prediction through Hierarchical Feature Learning. In 2025 IEEE/ACS 22nd International Conference on Computer Systems and Applications (AICCSA) (pp. 1-6). IEEE. https://doi.org/10.1109/AICCSA66935.2025.113151892025
89Sajid, M., Latif, S., Zafar, Z. & Fraz, M.M., 2025. Few-shot multilingual coreference resolution using long-context large language models. Proceedings of the Eighth Workshop on Computational Models of Reference, Anaphora and Coreference, pp.154–162, Suzhou, China. Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.crac-1.142025
88Athar, U., Ali, M., Zafar, Z., Khurshid, H., Berns, K. and Fraz, M.M., 2025, May. Sunflower Lodging Detection and Monitoring Through UAV-Based Multispectral Data. In 2025 International Conference on Innovation in Artificial Intelligence and Internet of Things (AIIT) (pp. 1-7). IEEE. https://doi.org/10.1109/AIIT63112.2025.110828882025
87Hassan, T.U., Khurram, A.B., Iqbal, S., Malik, A.W. and Fraz, M.M., 2024, December. Resolving Community Parking Issues: An IoT Enabled Statistical and Deep Learning Approach for Enhanced Urban Parking Management. In 2024 International Conference on Frontiers of Information Technology (FIT) (pp. 1-6). IEEE. https://doi.org/10.1109/FIT63703.2024.108384402024
86Athar, U., Ali, M., Zafar, Z., Khurshid, H., Berns, K. and Fraz, M.M., 2024, December. Merging UAV-Derived Metrics with Crop Physiology to Estimate Sunflower Yield. In 2024 International Conference on Frontiers of Information Technology (FIT) (pp. 1-6). IEEE. https://doi.org/10.1109/FIT63703.2024.108384002024
85Arif, H., Bilal, H.S.M., Satti, F.A., Ali, S.I. and Fraz, M.M., 2024, December. Cross-Platform Integration in Legacy Mobile Apps for Code Reuse and Reduced Development Efforts. In 2024 International Conference on Frontiers of Information Technology (FIT) (pp. 1-6). IEEE. https://doi.org/10.1109/FIT63703.2024.108383482024
84Aftab, K., Qudsia, M., Athar, U. and Fraz, M.M., 2024, November. Analyzing Fish Wellness Using Spatiotemporal Data & Behavior Recognition. In 2024 19th International Conference on Emerging Technologies (ICET) (pp. 1-7). IEEE.https://doi.org/10.1109/ICET63392.2024.109351732024
83Ali, M., Athar, U., Zafar, Z., Berns, K. and Fraz, M.M., 2024, November. Water Stress Diagnosis in Rainfed Wheat Through UAV Multispectral Imagery and IoT Data. In 2024 19th International Conference on Emerging Technologies (ICET) (pp. 1-7). IEEE.https://doi.org/10.1109/ICET63392.2024.109352872024
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81Sabah, N.U., Zafar, Z., Satti, F.A., Berns, K. and Fraz, M.M., 2024. Enhancing Cotton Crop Mapping in Pakistan: Integrating Transfer and Active Learning with Remote Sensing Technologies. In: 2024 4th International Conference on Digital Futures and Transformative Technologies (ICoDT2) , pp.1-8. IEEE. https://doi.org/10.1109/ICoDT262145.2024.107401962024
80Shami, U.A., Khan, B., Zafar, Z. and Fraz, M.M., 2024. Bridging the Resolution Gap in Remote Sensing: A Comparative Analysis of Deep Learning Models for Real-World Single Image Super-Resolution. In: 2024 4th International Conference on Digital Futures and Transformative Technologies (ICoDT2) , pp.1-8. IEEE. https://doi.org/10.1109/ICoDT262145.2024.107402592024
79Mehboob, F., Satti, F.A., Ali, S.I. and Fraz, M.M., 2024, October. Content-Aware Entity Alignment: Utilizing Structural and Semantic Similarities for Enhanced Inter-Knowledge Graph Integration. In 2024 4th International Conference on Digital Futures and Transformative Technologies (ICoDT2) (pp. 1-10). IEEE. https://doi.org/10.1109/ICoDT262145.2024.107402032024
78Khan, R., Khalid, M.A., Zulfiqar, K., Bashir, U. and Fraz, M.M., 2024. Enhanced Cephalometric Landmark Detection Using Multi-scale Feature Learning and Heatmap Regression. In: 2024 International Conference on Asia Pacific Advanced Network (APAN) , pp.29-41. Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-89813-6_32024
77Shami, U.A., Khan, B., Perwaiz, N., Zafar, Z. and Fraz, M.M., 2024. SPOTifying the Sentinel-2 Imagery: Harnessing the Power of Attention in Real World Single Image Super-Resolution. In: 2024 International Conference on Asia Pacific Advanced Network (APAN) , pp.13-28. Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-89813-6_22024
76Akhtar, M.S., Mahmood, Z., Fayyaz, M., Shami, U.A., Zafar, Z., Berns, K. and Fraz, M.M., 2024. Deciphering Crop Dynamics: Leveraging Field Geometry for Precise Image Registration and Enhanced Insights. In: 2024 International Conference on Asia Pacific Advanced Network (APAN) , pp.1-12. Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-89813-6_12024
75Khan, R., Khalid, M.A., Zulfiqar, K., Bashir, U. and Fraz, M.M., 2024, July. Enhancing cephalometric landmark detection with a two-stage cascaded CNN on multi-resolution multi-modal data. In Annual conference on medical image understanding and analysis(pp. 3-18). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-66958-3_12024
74Zafar, R., Khan, B. and Fraz, M.M., 2023, November. PakWaterSeg: A Multi-Temporal Satellite Water Bodies Dataset. In 2023 18th International Conference on Emerging Technologies (ICET) (pp. 287-292). IEEE. https://doi.org/10.1109/ICET59753.2023.103747572024
73Mehmood, V., Malik, A.I., Zafar, Z., Shahzad, M., Berns, K. and Fraz, M.M., 2023, October. Multi-year monitoring of wheat phenology and effect of climate change in the south Asian region using Sentinel-2 NDVI time series analysis. In Image and Signal Processing for Remote Sensing XXIX (Vol. 12733, pp. 208-219). SPIE. https://doi.org/10.1117/12.26831482023
72Mehmood, V., Murtaza, R., Zafar, Z., Shahzad, M., Berns, K. and Fraz, M.M., 2023, July. Time series-based active labeling framework for curating a multispectral sentinel 2 imagery dataset for crop type mapping. In IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium(pp. 3506-3509). IEEE. https://doi.org/10.1109/IGARSS52108.2023.102820842023
71Shahzad, K., Iqbal, S. and Fraz, M.M., 2023, June. Automated solution development for smart grids: Tapping the power of large language models. In 2023 17th International Conference on Engineering of Modern Electric Systems (EMES) (pp. 1-4). IEEE. https://doi.org/10.1109/EMES58375.2023.101716812023
70Amjad, H., Ashraf, M.S., Sherazi, S.Z.A., Khan, S., Fraz, M.M., Hameed, T. and Bukhari, S.A.C., 2023. Attention-Based Explainability Approaches in Healthcare Natural Language Processing. HEALTHINF, pp.689-696. https://doi.org/10.5220/001192730000341410.5220/00119273000034142023
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68Tariq, F., Khan, S.A. and Fraz, M.M., 2022, November. Learning Disease Specific Knowledge Graph from Unstructured Radiology Reports and Electronic Health Records (EHRs). In 2022 17th International Conference on Emerging Technologies (ICET) (pp. 101-106). IEEE. https://doi.org/10.1109/ICET56601.2022.100046792022
67us Sabah, N., Usama, M., Zafar, Z., Shahzad, M., Fraz, M.M. and Berns, K., 2022, November. Analysis of vegetation indices in the cotton crop in south asia region using uav imagery. In 2022 17th international conference on emerging technologies (ICET) (pp. 70-75). IEEE. https://doi.org/10.1109/ICET56601.2022.100046622022
66Rizvi, S.K.J. and Fraz, M.M., 2022, December. An efficient adversarial defiance towards malware detection system (mds). In 2022 IEEE 19th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) (pp. 178-182). IEEE. https://doi.org/10.1109/HONET56683.2022.100190762022
65Nasir, E.S. and Fraz, M.M., 2022, June. NuRISC: Nuclei Radial Instance Segmentation and Classification. In International Conference on Medical Imaging and Computer-Aided Diagnosis(pp. 37-51). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-16-6775-6_42022
64Tariq, F., Khan, S.A. and Fraz, M.M., 2022, June. Schema Based Knowledge Graph for Clinical Knowledge Representation from Structured and Un-structured Oncology Data. In International Conference on Medical Imaging and Computer-Aided Diagnosis(pp. 529-539). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-16-6775-6_432022
63Nawshad, M.A., Zafar, Z. and Fraz, M.M., 2022, October. Recognition of faces wearing masks using skip connection based dense units augmented with self restrained triplet loss. In 2022 24th International Multitopic Conference (INMIC) (pp. 1-7). IEEE. https://doi.org/10.1109/INMIC56986.2022.99729122022
62Perwaiz, N., Shahzad, M. and Fraz, M.M., 2022, October. Unveiling the potential of vision transformer architecture for person re-identification. In 2022 24th International Multitopic Conference (INMIC) (pp. 1-6). IEEE. https://doi.org/10.1109/INMIC56986.2022.99729082022
61Wazir, S. and Fraz, M.M., 2022, June. HistoSeg: Quick attention with multi-loss function for multi-structure segmentation in digital histology images. In 2022 12th International Conference on Pattern Recognition Systems (ICPRS) (pp. 1-7). IEEE. https://doi.org/10.1109/ICPRS54038.2022.98540672022
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58Rasool, A., Fraz, M.M. and Javed, S., 2021, May. Multiscale unified network for simultaneous segmentation of nerves and micro-vessels in histology images. In 2021 International conference on digital futures and transformative technologies (ICoDT2) (pp. 1-6). IEEE. https://doi.org/10.1109/ICoDT252288.2021.94415092021
57Dogar, G.M., Fraz, M.M. and Javed, S., 2021, May. Feature attention network for simultaneous nuclei instance segmentation and classification in histology images. In 2021 International conference on digital futures and transformative technologies (ICoDT2) (pp. 1-6). IEEE. https://doi.org/10.1109/ICoDT252288.2021.94414742021
56Nawshad, M.A., Shami, U.A., Sajid, S. and Fraz, M.M., 2021, May. Attention based residual network for effective detection of covid-19 and viral pneumonia. In 2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2) (pp. 1-7). IEEE. https://doi.org/10.1109/ICoDT252288.2021.94414852021
55Hashmi, T.S.S., Haq, N.U., Fraz, M.M. and Shahzad, M., 2021, May. Application of deep learning for weapons detection in surveillance videos. In 2021 international conference on digital futures and transformative technologies (ICoDT2) (pp. 1-6). IEEE. https://doi.org/10.1109/ICoDT252288.2021.94415232021
54Sattar, S., Sattar, Y., Shahzad, M. and Fraz, M.M., 2021, May. Group Activity Recognition in Visual Data: A Retrospective Analysis of Recent Advancements. In 2021 International Conference On Digital Futures And Transformative Technologies (ICoDT2) (pp. 1-8). IEEE. https://doi.org/10.1109/ICoDT252288.2021.94414782021
53Faizan, R., Fraz, M.M. and Shahzad, M., 2021, May. Iab-net: Informative and attention based person re-identification. In 2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2) (pp. 1-5). IEEE. https://doi.org/10.1109/ICoDT252288.2021.94414802021
52Khan, A.H., Fraz, M.M. and Shahzad, M., 2021, May. Deep learning based land cover and crop type classification: A comparative study. In 2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2) (pp. 1-6). IEEE. https://doi.org/10.1109/ICoDT252288.2021.94414832021
51Arshad, M.S., Rehman, U.A. and Fraz, M.M., 2021, May. Plant disease identification using transfer learning. In 2021 international conference on digital futures and transformative technologies (ICoDT2) (pp. 1-5). IEEE.https://doi.org/10.1109/ICoDT252288.2021.94415122021
50Shahid, A.M., Fraz, M.M. and Shahzad, M., 2021, May. Large scale face recognition in the wild: technical challenges and research directions. In 2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2) (pp. 1-7). IEEE. https://doi.org/10.1109/ICoDT252288.2021.94415252021
49Jamshed, A. and Fraz, M.M., 2021, May. NLP meets vision for visual interpretation-a retrospective insight and future directions. In 2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2) (pp. 1-8). IEEE. https://doi.org/10.1109/ICoDT252288.2021.94415172021
48Haq, N.U., Hashmi, T.S.S., Fraz, M.M. and Shahzad, M., 2021, May. Rotation aware object detection model with applications to weapons spotting in surveillance videos. In 2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2) (pp. 1-6). IEEE. https://doi.org/10.1109/ICoDT252288.2021.94415382021
47Qasim, H.S.A., Shahzad, M. and Fraz, M.M., 2021, May. Deep learning for face detection: Recent advancements. In 2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2) (pp. 1-6). IEEE. https://doi.org/10.1109/ICoDT252288.2021.94414762021
46Rashid, S.N., Fraz, M.M. and Javed, S., 2020, December. Multiscale dilated unet for segmentation of multi-organ nuclei in digital histology images. In 2020 IEEE 17th international conference on smart communities: improving quality of life using ICT, IoT and AI (HONET) (pp. 68-72). IEEE. https://doi.org/10.1109/HONET50430.2020.93228332020
45Aslam, W., Fraz, M.M., Rizvi, S.K. and Saleem, S., 2020, December. Cross-validation of machine learning algorithms for malware detection using static features of Windows portable executables: A Comparative Study. In 2020 IEEE 17th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) (pp. 73-76). IEEE. https://doi.org/10.1109/HONET50430.2020.93228092020
44Javed, U., Fraz, M.M., Mahmood, I., Shahzad, M. and Arif, O., 2020, December. Forecasting of electricity generation for hydro power plants. In 2020 IEEE 17th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) (pp. 32-36). IEEE. https://doi.org/10.1109/HONET50430.2020.93228412020
43Perwaiz, N., Fraz, M.M. and Shahzad, M., 2020, November. Smart visual surveillance: Proactive person re-identification instead of impulsive person search. In 2020 IEEE 23rd international multitopic conference (INMIC) (pp. 1-6). IEEE. https://doi.org/10.1109/INMIC50486.2020.93181072020
42Yaqoob, M.K., Ali, S.F., Kareem, I. and Fraz, M.M., 2020, November. Feature-based optimized deep residual network architecture for diabetic retinopathy detection. In 2020 IEEE 23rd International Multitopic Conference (INMIC) (pp. 1-6). IEEE. https://doi.org/10.1109/INMIC50486.2020.93180962020
41Bashir, R.S., Mahmood, H., Shaban, M., Raza, S.E.A., Fraz, M.M., Khurram, S.A. and Rajpoot, N.M., 2020, March. Automated grade classification of oral epithelial dysplasia using morphometric analysis of histology images. In Medical Imaging 2020: Digital Pathology (Vol. 11320, pp. 245-250). SPIE. https://doi.org/10.1117/12.25497052020
40Pervaiz, N., Fraz, M.M. and Shahzad;, M., 2019. Hierarchical Refined Local Associations for Robust Person Re-Identification. Proceedings of 3rd IEEE International Conference on Robotics and Automation, Islamabad, Pakistan. https://doi.org/10.1109/ICRAI47710.2019.89673892019
39Fraz, M.M., Shaban, M., Graham, S., Khurram, S. A. and Rajpoot, N. M., 2018. Uncertainty Driven Pooling Network for Microvessel Segmentation in Routine Histology Images. Proceedings of the 21st International Conference on Medical Image Computing and Computer Assisted Intervention, Sep 2018, Granada, Spain. https://doi.org/10.1007/978-3-030-00949-6_192018
38Javed, Sajid, Fraz, M.M., Epstein, David, Snead, David, Rajpoot, Nasir M. and Classification“, “Cellular Community Detection for Tissue, 2018. . Proceedings of the 21st International Conference on Medical Image Computing and Computer Assisted Intervention, Sep 2018, Granada, Spain. https://doi.org/10.1016/j.media.2020.1016962018
37Batool, S., Ali, M. Z., Shahzad, M. and Fraz, M. M., 2018. End to End Person Re-Identification for Automated Visual Surveillance. Proceedings of the International Conference on Image Processing, Applications and Systems (IPAS), Dec 2018, Sophia Antipolis, France. https://doi.org/10.1109/IPAS.2018.87088822018
36Anser, W., Fraz, M. M. and Shahzad, M., 2018. Two Stream Deep CNN-RNN Attentive Pooling Architecture for Video-based Person Re-identification. Proceedings of the 23rd Iberoamerican Congress on Pattern Recognition, Nov 2018, Madrid, Spain. https://doi.org/10.1007/978-3-030-13469-3_762018
35Bashir, R. M. S., Shahzad, M. and Fraz, M. M., 2018. DUPL-VR: Deep Unsupervised Progressive Learning for Vehicle Re-Identification. Proceedings of the 13th International Symposium on Visual Computing, Nov 2018, Las Vegas, United States. https://doi.org/10.1007/978-3-030-03801-4_262018
34Mubariz, Naima, Mumtaz, Saba, Hamayun, M. M. and Fraz, M. M., 2018. Optimization of Person Re-Identification through Visual Descriptors. Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Jan, 2018, Funchal, Madeira, Portugal. https://doi.org/10.5220/00066133034803552018
33Kamran, F., Shahzad, M. and Shafait, F., 2018. Automated Military Vehicle Detection from Low-Altitude Aerial Images. Proceedings of the Digital Image Computing: Techniques and Applications (DICTA), Dec, 2018, Canberra, Australia. https://doi.org/10.1109/DICTA.2018.86158652018
32M.Shahzad, Maurer, M., Fraundorfer, F., Wang, Y. and Zhu, X. X., 2018. Extraction of buildings in vhr SAR images using fully convolution neural networks. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul 2018, Valencia,Spain. https://doi.org/10.1109/IGARSS.2018.85196032018
31AlBadawi, Sufian and Fraz, M.M., 2018. Arterioles and Venules Classification in Retinal Images Using Fully Convolutional Deep Neural Network. Proceedings of the 15th International Conference Image Analysis and Recognition, Jun 2018, Póvoa de Varzim, Portugal. https://doi.org/10.1007/978-3-319-93000-8_752018
30Bader, M., Shahzad, M. and Fraz, M. M., 2018. Simultaneous Segmentation of Multiple Retinal Pathologies Using Fully Convolutional Deep Neural Network. Proceedings of the 22nd Conference on Medical Image Understanding and Analysis 2018, Jul 2018, Southempton, United Kingdom. https://doi.org/10.1007/978-3-319-95921-4_292018
29Khurram, I., Fraz, M. M. and Shahzad, M., 2018. Detailed Sentence Generation Architecture for Image Semantics Description. Proceedings of the 13th International Symposium on Visual Computing, Nov 2018, Las Vegas, United States. https://doi.org/10.1007/978-3-030-03801-4_372018
28Mumtaz, S., Mubariz, N., Saleem, S. and Fraz, M. M., 2017. Weighted hybrid features for person re-identification. Proceedings of the 7th International Conference on Image Processing Theory, Tools and Applications (IPTA), 2017, Dec, 2017, Montreal, QC, Canada. https://doi.org/10.1109/IPTA.2017.83101072017
27Sun, Y., Shahzad, M. and Zhu, X. X., 2017. Building Height Estimation in Single SAR image using OSM building footprints. Proceedings of the Joint Urban Remote Sensing Event (JURSE), Mar, 2017, Dubai, United Arab Emirates. https://doi.org/10.1109/JURSE.2017.79245492017
26Shahzad, M., Zhu, X. X. and Bamler, R., 2016. Façade structure reconstruction using spaceborne TomoSAR point clouds. Proceedings of the IEEE Geoscience and Remote Sensing Symposium (IGARSS), Jan 2016, Munich, Germany. https://doi.org/10.1109/IGARSS.2012.63513852016
25Zhu, X. X., Ge, N. and Shahzad, M., 2016. Group Sparsity in SAR Tomography – Experiments on TanDEM-X Data Stacks. Proceedings of the 16th International Radar Symposium (IRS), Jan, 2016, Dresden,Germany. https://doi.org/10.1109/IRS.2015.72263542016
24Zhu, X. X., Ge, N. and Shahzad, M., 2016. Exploiting Group Sparsity in SAR Tomography. Proceedings of the 3rd International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing (CoSeRa), Jan 2016, Pisa, Italy. https://doi.org/10.1109/CoSeRa.2015.73302552016
23Sun, Y., Shahzad, M. and Zhu, X. X., 2016. First prismatic building model reconstruction from TomoSAR point clouds. Proceedings of the XXIII ISPRS Congress 2016, Prague, Czech Republic, Jan 2016, Prague,Czech Republic. https://doi.org/10.5194/isprs-archives-XLI-B3-381-20162016
22Schmitt, M., Shahzad, M. and Zhu, X. X., 2016. Forest remote sensing on the individual tree level by airborne millimeterwave SAR. Proceedings of the IEEE Geoscience and Remote Sensing Symposium (IGARSS), 2016, Beijing, China, Jan 2016, Beijing, China. https://doi.org/10.1109/IGARSS.2016.77290302016
21Shahzad, M., Schmitt, M. and Zhu, X. X., 2015. Segmentation and crown parameter extraction of individual trees in an airborne TomoSAR point cloud. Proceedings of the PIA15+HRIGI15 – Joint ISPRS conference, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-3/W2, 2015, Jan 2015, Munich, Germany. https://doi.org/10.5194/isprsarchives-XL-3-W2-205-20152015
20Shahzad, M. and Zhu, X. X., 2015. Detection Of Buildings In Spaceborne TomoSAR Point Clouds Via Hybrid Region Growing And Energy Minimizatison Technique. Proceedings of the Joint Urban Remote Sensing Conference (JURSE), Jan 2015, Lausanne, Switzerland. https://doi.org/10.1109/JURSE.2015.71204802015
19Abdullah, M. and Fraz, M. M., 2015. Application of grow cut algorithm for localization and extraction of optic disc in retinal images. Proceedings of the 12th International Conference on High-capacity Optical Networks and Enabling/Emerging Technologies (HONET), Dec 2015, Islamabad, Pakistan. https://doi.org/10.1109/HONET.2015.73954362015
18Welikala, R.A., Fraz, M.M., Hayat, S., Rudnicka, A.R., Foster, P.J., Whincup, P.H., Owen, C.G., Strachan, D.P. and Barman, S.A., 2015. Automated retinal vessel recognition and measurements on large datasets. Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015 Aug, 2015, Milan,Italy. https://doi.org/10.1109/EMBC.2015.73195732015
17Shahzad, M. and Zhu, X. X., 2014. Automatic Large Area Reconstruction of Building Facades from Spaceborne TomoSAR Point Clouds. Proceedings of the IEEE Geoscience and Remote Sensing Symposium (IGARSS), Jan 2014, Quebec, Canada. https://doi.org/10.1109/IGARSS.2014.69467342014
16Shahzad, M. and Zhu, X. X., 2014. Reconstructing 2-D/3-D Building Shapes From Spaceborne Tomographic SAR Point Clouds. Proceedings of the Photogrammetric Computer Vision (PCV), International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences – ISPRS Technical Commission III Symposium, Jan 2014,,Switzerland. https://doi.org/10.5194/isprsarchives-XL-3-313-20142014
15Zhu, X. X., Wang, Y., Shahzad, M. and Bamler, R., 2014. Spaceborne TomoSAR and Beyond: From SAR Image Stacks to Objects. Proceedings of the 10th European Conference on Synthetic Aperture Radar (EUSAR), Jan 2014, Berlin, Germany. https://ieeexplore.ieee.org/abstract/document/68570512014
14Fraz, M.M., Rudnicka, A.R., Owen, C.G., Strachan, D.P. and Barman, S.A., 2014. Automated Arteriole and Venule Recognition in Retinal Images using Ensemble Classification. Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISAAP), Jan 2014, Lisbon, Portugal. https://ieeexplore.ieee.org/abstract/document/72950802014
13Shahzad, M. and Zhu, X. X., 2013. Building façades reconstruction using multi-view tomosar point clouds. Proceedings of the Joint Urban Remote Sensing Event (JURSE), Jan 2013, Sao Paulo, Brazil. https://doi.org/10.1109/JURSE.2013.65506912013
12Shahzad, M. and Zhu, X. X., 2013. Robust Building Facade Reconstruction from Spaceborne TomoSAR Points. Proceedings of the CMRT13 – City Models, Roads and Traffic 2013 – ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Jan 2013, Antalya, Turkey. https://elib.dlr.de/86149/2013
11Zhu, X. X., Shahzad, M., Wang, Y. and Bamler, R., 2013. Tomographic Urban Imaging Using TerraSAR-X High Resolution Spotlight Data Stacks. Proceedings of the ESA Living Planet Symposium 2013 Jan, Edinburgh, United Kingdom. https://mediatum.ub.tum.de/14357622013
10Shahzad, M. and Zhu, X. X., 2013. Reconstruction of Building Facades Using Spaceborne Multiview TomoSAR Point Clouds. Proceedings of the IEEE Geoscience and Remote Sensing Symposium (IGARSS), Jan 2013, Melbourne, Australia. https://doi.org/10.1109/IGARSS.2013.67212342013
9Fraz, M.M., Remagnino, P., Hoppe, A. and Barman, S.A., 2013. Retinal image analysis aimed at extraction of vascular structure using linear discriminant classifier. Proceedings of the IEEE International Conference on Computer Medical Applications ICCMA’ 2013, Jan 2013, Sousse, Tunisia. https://doi.org/10.1109/ICCMA.2013.65061802013
8Shahzad, M. and Zhu, X. X., 2012. From TomoSAR Point Clouds to Objects: Facade Reconstruction. Proceedings of the Tyrrhenian Workshop on Advances in Radar and Remote Sensing (TyWRRS), Jan 2012, Naples, Italy. https://doi.org/10.1109/TyWRRS.2012.63811132012
7Fraz, M.M., Remagnino, P., Hoppe, A., Uyyanonvara, B., Rudnicka, A., Owen, C.G. and Barman, S.A., 2012. Retinal vessel segmentation using ensemble classifier of bagged decision trees. Proceedings of the IET Conference on Image Processing, Jul 2012, London, United Kingdom. https://doi.org/10.1049/cp.2012.04582012
6Fraz, M.M., Remagnino, P., Hoppe, A., Rudnicka, A., Owen, C.G., Whincup, P. H. and Barman, S.A., 2012. A model based approach for vessel calibre measurement in retinal images. Proceedings of the 8th International Conference on Signal Image Technology & Internet Based Systems (SITIS), Nov 2012, Sorrento, Italy. https://doi.org/10.1109/SITIS.2012.292012
5Fraz, M.M., Basit, A., Remagnino, P., Hoppe, A. and Barman, S.A., 2011. Retinal vasculature segmentation by morphological curvature, reconstruction and adapted hysteresis thresholding. Proceedings of the 7th International Conference on Emerging Technologies (ICET 2011), Sep 2011, Islamabad, Pakistan. https://doi.org/10.1109/ICET.2011.60484872011
4Fraz, M.M., Remagnino, P., Hoppe, A., Velastin, S., Uyyanonvara, B. and Barman, S.A., 2011. A Supervised Method for Retinal Blood Vessel Segmentation Using Line Strength, Multiscale Gabor and Morphological Features. Proceedings of the IEEE International Conference on Signal & Image Processing Applications, Nov 2011,Kuala Lumpur, Malaysia. https://doi.org/10.1109/ICSIPA.2011.61441292011
3Fraz, M.M., Javed, M.Y. and Basit, A., 2008. Evaluation of Retinal Vessel Segmentation Methodologies Based on Combination of Vessel Centerlines and Morphological Processing. Proceedings of the 4th IEEE International Conference on Emerging Technologies (ICET 2008), Oct 2008, Islamabad, Pakistan. https://doi.org/10.1109/ICET.2008.47775062008
2Fraz, M.M., Javed, M.Y. and Basit, A., 2008. Retinal Vessels Extraction Using Bitplanes. Proceedings of the 8th IASTED International Conference on Visualization, Imaging, and Image Processing, Sep 2008, Palma De Mallorca, Spain. https://www.actapress.com/Abstract.aspx?paperId=339222008
1Jan, M.A., Zahid, F.A., Fraz, M.M. and Ali, Arshad, 2003. Exploiting peer group concept for adaptive and highly available services. Proceedings of the Computing in High Energy and Nuclear Physics (CHEP 03), Mar 2003, La Jolla California, United States. https://eprints.kingston.ac.uk/id/eprint/168432003

Book/Chapter

#Book/ChapterYear
7M.A, Nawshad, M.M. Fraz (2023). Improving Masked Face Recognition Using Dense Residual Unit Aided with Quadruplet Loss. In: Yan, W.Q., Nguyen, M., Stommel, M. (eds) Image and Vision Computing. IVCNZ 2022. Lecture Notes in Computer Science, vol 13836. Springer, Cham. https://doi.org/10.1007/978-3-031-25825-1_252023
6M.M. Fraz, Shaban, M., Graham, S., Khurram, S.A., Rajpoot, N.M. (2018). Uncertainty Driven Pooling Network for Microvessel Segmentation in Routine Histology Images. In: , et al. Computational Pathology and Ophthalmic Medical Image Analysis. OMIA COMPAY 2018 2018. Lecture Notes in Computer Science, vol 11039. Springer, Cham. https://doi.org/10.1007/978-3-030-00949-6_192018
5Bashir, R.M.S., Shahzad, M., Fraz, M.M. (2018). DUPL-VR: Deep Unsupervised Progressive Learning for Vehicle Re-Identification. In: , et al. Advances in Visual Computing. ISVC 2018. Lecture Notes in Computer Science, vol 11241. Springer, Cham. https://doi.org/10.1007/978-3-030-03801-4_262018
4AlBadawi, S., Fraz, M.M. (2018). Arterioles and Venules Classification in Retinal Images Using Fully Convolutional Deep Neural Network. In: Campilho, A., Karray, F., ter Haar Romeny, B. (eds) Image Analysis and Recognition. ICIAR 2018. Lecture Notes in Computer Science, vol 10882. Springer, Cham. https://doi.org/10.1007/978-3-319-93000-8_75
2018
3Khurram, I., Fraz, M.M., Shahzad, M. (2018). Detailed Sentence Generation Architecture for Image Semantics Description. In: , et al. Advances in Visual Computing. ISVC 2018. Lecture Notes in Computer Science(), vol 11241. Springer, Cham. https://doi.org/10.1007/978-3-030-03801-4_372018
2M.M. Fraz, S.A. Barman, "Computer vision algorithms applied to retinal vessel segmentation and quantification of vessel calibre", in Image Analysis and Modelling in Ophthalmology by CRC Press Tayler and Francis, ISBN 978-1-4665-5938, Feb, 2014.2014
1M.M. Fraz, S.A. Barman, "Image Analysis and Modelling in Ophthalmology / Ensemble classification applied to retinal blood vessel segmentation: Theory and Implementation", in Image Analysis and Modelling in Ophthalmology by CRC Press Tayler and Francis, ISBN 978-1-4665-5938, Feb, 2014.2014

Patent List

#TitleInventorsRegistered Date
24Enhancing Single Image Super Resolution for Real World Remote Sensing Imagery (Reg No 57834-Copr)Usama Aleem Shami, Muhammad Moazam Fraz9th June 2026
23Wheat Mapping from satellite Time Series Leveraging Superpixel-Based Active Learning for Data Sparse Regions Across Multiple Years (Reg No 50544-Copr)Muhammad Moazam Fraz, Vaneeza Mehmood9th April 2024
22A Self Supervised Based Deep Learning Model for Survival Analysis of Tumorigenesis Patients Using Whole Slide Image (Reg. No 50543-Copr)Muhammad Moazam Fraz, Arshi Pervaiz9th April 2024
21Improving Image Super Resolution Using Squeeze-and-Residual-Excitation with Holistic Attention in Deep Neural Networks (Reg. No 50245-Cpor)Muhammad Moazam Fraz, Muhammad Shahzad, Bostan Khan26th Feb 2024
20Information Attention Based Person Re-Identification for Automated Surveillance (Reg. No. 50246-Copr)Muhammad Moazam Fraz, Muhammad Shahzad26th Feb 2024
19An Attention based Distance Regression CNN for Nuclei Instance Segmentation and Type Classification (Reg. No. 50247-Copr)Muhammad Moazam Fraz, Muhammad Shahzad, Ghulam Murtaza Dogar26th Feb 2024
18Orientation Aware Weapons Detection in Visual Data (Reg. No. 50248-Copr)Muhammad Moazam Fraz, Muhammad Shahzad, Nazeef Ul Haq, Tufail Sajjad26th Feb 2024
17Knowledge-Aware Visual Question Answering Framework for developing visual learning apps for children (Reg. No. 49158-Copr)Muhammad Moazam Fraz, Ahmed Jamshed14th Sep 2023
16Live News Channels Stream Analytics Framework (Reg. No. 49159-Copr)Muhammad Moazam Fraz, Muhammad Ehsan Ul Haq, Muhammad Shahzad14th Sep 2023
15Disease Specific Knowledge Graphs for Unstructured EMRs and Radiology Reports (Reg. No. 49274-Copr)Muhammad Moazam Fraz, Farina Tariq, Saad Ahmad Khan27th Sep 2023
14ActiPhe: A deep Active Learning Framework for Cancer Phenotypes Labelling in Unstructured EHRs (Reg. No. 49808-Copr)Saad Ahmad Khan, Muhammad Moazam Fraz15th Dec 2023
13Static analysis based progressive framework for deep unsupervised malware classification of Windows portable executable (Reg. No. 44160-Copr)Muhammad Moazam Fraz, Syed Khurram Jah Rizvi30th Sep 2021
12Stochastic Attentions and Context Learning for Person Re-Identification in Surveillance Data
Muhammad Moazam Fraz, Nazia Pervaiz30th Sep 2021