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Paper accepted for publication in the IEEE Transactions on Systems, Man, and Cybernetics: Systems

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Collaborating with Nanjing University of Science and Technology (NUST), Panasonic R&D Center Singapore co-authored a paper titled “Modular Lightweight Network for Road Object Detection using a Feature Fusion Approach”, which has been accepted for publication in the IEEE Transactions on Systems, Man, and Cybernetics: Systems. The paper presents a modular lightweight Deep Learning model for detection of road objects such as cars, pedestrians and cyclists. In a situation where objects are far away from the camera and small in size, we utilize a fast and efficient network architecture, referred to as modular feature fusion detector (MFFD), to give evidence of the improvement of ThinNet.