Deep Convolutional Neural Networks for Identification, Tracking, and Classification of Transport Vehicles using Multiple-view Imaging Systems

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This project revolves around the concept of Identification, Tracking, and Classification (ITC) of transport vehicles passing through inspection stations using imaging sensors. Multiple-view machine-learning-based algorithms will be developed that is robust to partial occlusion in the imaging sensors and to the light scatter due to differential illumination and weather conditions for the first time. A close collaboration between IRD and the University of Regina (UofR) will generate a unique partnership between industry and academia that can pave the way towards training highly-qualified personnel at both institutes. Furthermore, the transport vehicle inspection facilities, such as the one in the Global Transportation Hub (GTH) will be used as a living lab located at close proximity to the UofR, where our research results and findings can be tested and utilized. This project has the potential to lead to developing an emerging engineering discipline in intelligent transportation in Saskatchewan for the first time.