Stress Detection via Multimodal Multitemporal-Scale Fusion: A Hybrid of Deep Learning and Handcrafted Feature Approach-Reference-Cited by-同舟云学术

Stress Detection via Multimodal Multitemporal-Scale Fusion: A Hybrid of Deep Learning and Handcrafted Feature Approach

Author:

Zhao Liang¹^ORCID,Niu Xiaojing²,Wang Lincong³,Niu Jiale³^ORCID,Zhu Xiaoliang¹^ORCID,Dai Zhicheng¹^ORCID

Affiliation:

1. National Engineering Research Center of Educational Big Data (NERC-EBD), Central China Normal University (CCNU), Wuhan, China

2. National Engineering Research Center for E-Learning (NERCEL), Central China Normal University (CCNU), Wuhan, China

3. Faculty of Artificial Intelligence in Education, Central China Normal University (CCNU), Wuhan, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Ministry of Education of Humanities and Social Science Project

Hubei Provincial Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

AI and Faculty Empowerment Pilot Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

Reference91 articles.

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