Citation

Tay, Nian Chi and Tee, Connie and Pang, Ying Han (2022) Few-shot Learning for Human Activity Recognition and Anomaly Detection. In: Postgraduate Colloquium December 2022, 1-15 December 2022, Multimedia University, Malaysia. (Unpublished)

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Abstract

To formulate human activity recognition and anomaly detection methods with limited number of training data. •To propose a human activity reconstruction approach that can effectively locate primary human activity from a series of fine-grained secondary activities. •To evaluate the performance of the proposed human activity recognition and anomaly detection approaches.

Item Type:	Conference or Workshop Item (Poster)
Uncontrolled Keywords:	Human Activity Recognition
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	27 Dec 2022 03:09
Last Modified:	27 Dec 2022 03:09
URII:	http://shdl.mmu.edu.my/id/eprint/11014

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