Fatigue Detection for Ship OOWs Based on Input Data Features, From the Perspective of Comparison With Vehicle Drivers: A Review-Reference-Cited by-同舟云学术

Fatigue Detection for Ship OOWs Based on Input Data Features, From the Perspective of Comparison With Vehicle Drivers: A Review

Author:

Lyu Hongguang¹^ORCID,Yue Jingwen¹^ORCID,Zhang Wenjun¹,Cheng Tao²^ORCID,Yin Yong¹,Yang Xue¹,Gao Xiaowei²^ORCID,Hao Zengrui¹,Li Jiawei¹

Affiliation:

1. School of Navigation College, Dalian Maritime University, Dalian, China

2. SpaceTimeLab, Department of Civil, Environmental and Geomatic Engineering, University College London, London, U.K

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

Reference96 articles.

2. A detection algorithm for the fatigue of ship officers based on deep learning technique;wang;J Transp Inf Saf,2022

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