Vehicular Traffic Flow Parameter Estimation
Traffic analysis provide information to improving the efficiency of roadway transportation. Intelligent transportation systems (ITS) have attracted considerable research attention in areas such as vehicle detection, recognition, and counting, traffic flow control, lane change behavior, and traffic parameter estimation. In light of the anticipated availability of low-cost hardware, as well as continuing progress in algorithmic research, computer vision has become a promising base technology for traffic sensing systems. Since vision sensors provide more information than the conventional sensors widely used in ITS, attention is now being focused on vision-based traffic surveillance systems. The use of drone/unmanned aerial vehicles enable us to capture the traffic data, detecting vehicle and extracting the traffic parameter.
In big picture, we envision to develop next generation of Computational Pathology based tools and technologies that can be used in clinical practice enabling improved diagnosis, grading, prognosis, and treatment planning of cancer patients.