Open AccessInvestigation of changes in the operator’s state by analyzing the characteristics of blinking
Author(s) -
Vladimir Yurko,
A. B. Uali,
A. Naukenova
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1027/1/012030
Subject(s) - operator (biology) , convolutional neural network , artificial intelligence , computer science , state (computer science) , pattern recognition (psychology) , speech recognition , algorithm , chemistry , biochemistry , repressor , transcription factor , gene
This paper discusses in detail an approach using the method of automatic blink recognition for assessing the state of the operator using deep convolutional neural networks. It also analyzes the characteristics of blinking to detect the facts of loss of concentration.