Study of Deep Learning-based Hand Gesture Recognition Toward the Design of a Low-cost Prosthetic Hand

Saikawa Yamato; Abderazek Ben Abdallah

doi:10.1051/shsconf/202213903006

All issues

Volume 139 (2022)

SHS Web Conf., 139 (2022) 03006

References

Open Access

Issue		SHS Web Conf. Volume 139, 2022 The 4^th ETLTC International Conference on ICT Integration in Technical Education (ETLTC2022)


Article Number		03006
Number of page(s)		8
Section		Topics in Computer Science
DOI		https://doi.org/10.1051/shsconf/202213903006
Published online		13 May 2022

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[1] Ray Antonius and Hendra Tjahyadi. Electromyography Gesture Identification Using CNN-RNN Neural Network for Controlling Quadcopters. Journal of Physics, July(2021). [Google Scholar]

[2] Andrea Sarasola-Sanz, Nerea Irastorza-Landa, Eduardo López-Larraz, Carlos Bibián, Florian Helmhold, Doris Broetz,iels Birbaumer, Ander Ramos-Murguialday. A hybrid brain-machine interface based on EEG and EMG activity for the motor rehabilitation of stroke patients. International Conference on Rehabilitation Robotics (ICORR), July(2017). [Google Scholar]

[3] Division of Computer Engineering Ben Abdallah Laboratory http://web-ext.uaizuac.jp/misc/benablab/projects.html. [Google Scholar]

[4] TensorFlow https://www.tensorflow.org/?hl=ja. [Google Scholar]

[5] Naoto Ageishi. Design of Hand Gesture Recognition based on Deep Neural for Deep Learning., (2020). [Google Scholar]

[6] Connor Shorten and Taghi M. Khoshgoftaar. A survey on Image Data Augmentation for Deep Learning. Journal of Big Data, volume 6, July (2019). [Google Scholar]

[7] Shaofeng Cai, Yao Shu, Gang Chen, Beng Chin Ooi, Wei Wang, Meihui Zhang. Effective and Efficient Dropout for Deep Convolutional Neural Networks for Deep Learning. IEEE, July(2020). [Google Scholar]