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Deep-Learning-Based Remote Photoplethysmography Measurement in Driving Scenarios with Color and Near-Infrared Images
Li Wen Chiu, Yang Ren Chou, Yi Chiao Wu,
Bing Fei Wu
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電控工程研究所
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引文 斯高帕斯(Scopus)
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Keyphrases
Deep Learning
100%
Near-infrared Image
100%
Remote Photoplethysmography (rPPG)
100%
Colour Infrared
100%
Driving Scenarios
100%
Blue-green
75%
Heart Rate Estimation
75%
Root Mean Square Error
50%
Rainy Days
50%
Time Variation
25%
Wearable Devices
25%
State-of-the-art Techniques
25%
Adaptation
25%
Head Motion
25%
Public Dataset
25%
Varying Illumination
25%
Popular Topics
25%
Estimation Approaches
25%
Effective Alternative
25%
Vital Signs Monitoring
25%
Open Dataset
25%
Challenging Cases
25%
Monochrome
25%
Deep Learning Model
25%
Remote Vital Signs
25%
Motion Conditions
25%
Remote Vital Sign Monitoring
25%
Cross-dataset
25%
Build-up Rate
25%
Driver Monitoring
25%
Additional Head
25%
Weather Variability
25%
Computer Science
Deep Learning Method
100%
Experimental Result
50%
Wearable Device
50%
Varying Illumination
50%
RGB Image
50%
Deep Learning Model
50%
Practical Condition
50%
Engineering
Deep Learning Method
100%
Root Mean Square Error
66%
Vital Sign
66%
Experimental Result
33%
Wearable Sensor
33%
State-of-the-Art Method
33%
RGB Image
33%
Chemical Engineering
Deep Learning Method
100%