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Some Contemporary Approaches for Human Activity Recognition: A Survey

dc.contributor.authorSingh R.; Srivastava R.
dc.date.accessioned2025-05-23T11:31:15Z
dc.description.abstractHuman activity recognition(HAR) in video analysis has been an prominent area of research in the field of computer vision due to its large span of applications like intelligent surveillance systems, robot learning, Human Computer Interaction(HCI), health care. An activity recognition in video involve a large amount of data to be processed making it a challenging task. In the recent years, researchers have proposed several model using deep learning with different input modalities. This paper presents an analytical survey of recent deep learning models on the basis of input modality, feature extraction, classification, dataset used and accuracy. © 2020 IEEE.
dc.identifier.doihttps://doi.org/10.1109/PARC49193.2020.236672
dc.identifier.urihttp://172.23.0.11:4000/handle/123456789/13088
dc.relation.ispartofseries2020 International Conference on Power Electronics and IoT Applications in Renewable Energy and its Control, PARC 2020
dc.titleSome Contemporary Approaches for Human Activity Recognition: A Survey

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