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Transformers are state-of-the-art networks for most sequence processing tasks.
Comparison of six electromyography acquisition setups on hand movement classification tasks
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Evaluation of gated-recurrent unit for estimating finger-joint angle using surface electromyography signal
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SuperSpike: Supervised learning in multilayer spiking neural networks
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A million spiking-neuron integrated circuit with a scalable communication network and interface
Paul A. Merolla, John V. Arthur, Rodrigo Alvarez-Icaza, Andrew S. Cassidy, Jun Sawada, Filipp Akopyan, Bryan L. Jackson, Nabil Imam, Chen Guo, Yutaka Nakamura, Bernard Brezzo, Ivan Vo, Steven K. Esser, Rathinakumar Appuswamy, Brian Taba, Arnon Amir, Myron D. Flickner, William P. Risk, Rajit Manohar, and Dharmendra S. Modha
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Real-time hand gesture recognition using surface electromyography and machine learning: A systematic literature review
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Evaluation of feature extraction techniques and classifiers for finger movement recognition using surface electromyography signal
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