0000000001286397

AUTHOR

Simen B. Skriubakken

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Deep Learning-Based Sign Language Digits Recognition From Thermal Images With Edge Computing System

2021

The sign language digits based on hand gestures have been utilized in various applications such as human-computer interaction, robotics, health and medical systems, health assistive technologies, automotive user interfaces, crisis management and disaster relief, entertainment, and contactless communication in smart devices. The color and depth cameras are commonly deployed for hand gesture recognition, but the robust classification of hand gestures under varying illumination is still a challenging task. This work presents the design and deployment of a complete end-to-end edge computing system that can accurately provide the classification of hand gestures captured from thermal images. A th…

PixelComputer sciencebusiness.industryDeep learning010401 analytical chemistryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONRoboticsSign language01 natural sciences0104 chemical sciencesGesture recognitionComputer visionArtificial intelligenceElectrical and Electronic EngineeringbusinessInstrumentationEdge computingTest dataGestureIEEE Sensors Journal
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