Deep learning technology is often used for object detection. It has received attention recently because to the intimate connections between object detection, video analysis, and picture understanding. The goal of object detection has been pursued using a variety of models, and this is immensely beneficial to humanity. The most recent technical developments have helped the computational experiments, which would not have been conceivable if they had been tried using the conventional techniques. The powerful approaches employed in deep learning can show noticeably higher efficiency when compared to conventional designs and architectures. Numerous strategies and techniques have been used in deep learning to boost accuracy, and their drawbacks have also been somewhat addressed in order to lessen them. This study's main objective is to give an overview of several object detection procedures and approaches based on deep learning. Additionally, it lists the benefits and drawbacks of various object identification systems based on their potential applications and limitations.
Keywords
Deep Learning, Videos, Object Detection, RCNN, MRCNN.
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Cite this article
Kusuma S, Kiran P and Pavan Kumar S Kulkarni, “Deep Learning based Object Detection Techniques in Videos”, Advances in Intelligent Systems and Technologies, pp. 018-022. 2022. doi:10.53759/aist/978-9914-9946-0-5_3
