Abstract
Human activity recognition refers to predict what a person is doing from series of the observation of person’s action and surrounding conditions using different techniques. It is an active research area providing personalized support for various applications and its association with a wide range of fields of study like medicinal services, dependable automation developing, and smart surveillance system. This paper provides an overview which gives idea about some existing research methods on human activity recognition. It describes a general view on the state of the art for human activity recognition and shows comparative studies between existing research which consist of various methods, evaluation criteria, and features. It also comprises benefits and limitations of various methods to provide researchers to propose new approaches.
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Suthar, B., Gadhia, B. (2021). Human Activity Recognition Using Deep Learning: A Survey. In: Kotecha, K., Piuri, V., Shah, H., Patel, R. (eds) Data Science and Intelligent Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 52. Springer, Singapore. https://doi.org/10.1007/978-981-15-4474-3_25
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DOI: https://doi.org/10.1007/978-981-15-4474-3_25
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