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    Optimal Deep Convolutional Neural Network with Pose Estimation for Human Activity Recognition

    S. Nandagopal1,*, G. Karthy2, A. Sheryl Oliver3, M. Subha4

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1719-1733, 2023, DOI:10.32604/csse.2023.028003

    Abstract Human Action Recognition (HAR) and pose estimation from videos have gained significant attention among research communities due to its application in several areas namely intelligent surveillance, human robot interaction, robot vision, etc. Though considerable improvements have been made in recent days, design of an effective and accurate action recognition model is yet a difficult process owing to the existence of different obstacles such as variations in camera angle, occlusion, background, movement speed, and so on. From the literature, it is observed that hard to deal with the temporal dimension in the action recognition process. Convolutional neural network (CNN) models could… More >

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