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MOTION LEARNING USING SPATIO-TEMPORAL NEURAL NETWORK
2020
Journal of Information and Communication Technology
Motion trajectory prediction is one of the key areas in behaviour and surveillance studies. Many related successful applications have been reported in the literature. However, most of the studies are based on sigmoidal neural networks in which some dynamic properties of the data are overlooked due to the absence of spatiotemporal encoding functionalities. Even though some sequential (motion) learning studies have been proposed using spatiotemporal neural networks, as in those sigmoidal neural
doi:10.32890/jict2020.19.2.3
fatcat:sipaaohaubgmdnbxcztmjpdvpa