Gesture recognition using a bioinspired learning architecture that integrates visual data with somatosensory data from stretchable sensors

Gesture recognition using a bioinspired learning architecture that integrates visual data with somatosensory data from stretchable sensors

Gesture recognition using machine learning methods is valuable in the development of advanced cybernetics, robotics, and healthcare systems, and typically relies on images or videos. To improve recognition accuracy, such visual data can be fused with data from other sensors, but this approach is lim...

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Bibliographic Details
Main Authors: Wang, Ming, Yan, Zheng, Wang, Ting, Cai, Pingqiang, Gao, Siyu, Zeng, Yi, Wan, Changjin, Wang, Hong, Pan, Liang, Yu, Jiancan, Pan, Shaowu, He, Ke, Lu, Jie, Chen, Xiaodong
Other Authors: School of Materials Science and Engineering
Format: Journal Article
Language:English
Published: 2021
Subjects:
Engineering::Materials
Convolutional Neural Networks
Network architecture
Online Access:https://hdl.handle.net/10356/148021

Internet

https://hdl.handle.net/10356/148021

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