Negative Selection by Clustering for Contrastive Learning in Human Activity Recognition-Reference-Cited by-同舟云学术

Negative Selection by Clustering for Contrastive Learning in Human Activity Recognition

Author:

Wang Jinqiang¹^ORCID,Zhu Tao¹^ORCID,Chen Liming Luke²^ORCID,Ning Huansheng³^ORCID,Wan Yaping¹^ORCID

Affiliation:

1. School of Computer Science, University of South China, Heyang, China

2. Ulster University, Belfast, U.K

3. School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hunan Province

Research Foundation of Education Bureau of Hunan Province

Hengyang Science and Technology Major Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

Reference49 articles.

1. Learning representations by maximizing mutual information across views;bachman;Proc Int Conf Adv Neural Inf Process Syst,2019

3. A framework for contrastive self-supervised learning and designing a new approach;falcon;arXiv 2009 00104,2020

5. Deep learning for sensor-based human activity recognition: Overview, challenges, and opportunities;chen;ACM Comput Surv,2021

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