Datasets – Machine Vision & Intelligent Systems Lab

This dataset is presented to solve highly challenging problem of vehicle detection from high-resolution remote sensing imagery by introducing a novel medium size annotated dataset named Satellite Imagery Multivehicles Dataset (SIMD). The dataset images are acquired from multiple locations in the EU/US regions available in the public Google Earth satellite imagery. Specifically, it comprises 5000 images of resolution 1024 × 768 and collectively contains 45 096 objects in 15 different classes of vehicles including cars, trucks, buses, long vehicles, various types of aircrafts, and boats.

M. Haroon, M. Shahzad, M. M. Fraz , “Multi-sized Object Detection Using Spaceborne Optical Imagery”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), Vol. 13 , No. -, PP. 3032 – 3046, Jun, 2020: DOI: 10.1109/JSTARS.2020.3000317

Automatic detection of weapons is significant for improving security and well-being of individuals, nonetheless, it is a difficult task due to large variety of size, shape and appearance of weapons. View point variations and occlusion also are reasons which makes this task more difficult. Further, the current object detection algorithms process rectangular areas, however a slender and long rifle may really cover just a little portion of area and the rest may contain unessential details. To overcome these problems we propose Orientation Aware Weapons Detection algorithm which provides oriented bounding box and improved detection performance of weapons. The proposed model provides orientation not only using angle as classification problem by dividing angle into eight classes but also angle as regression problem.

N.U Haq, M.M. Fraz , T.S Hashmi, M. Shahzad, “Orientation Aware Weapons Detection In Visual Data : A Benchmark Dataset“, 2021, eprint arXiv https://arxiv.org/abs/2112.02221