Deep Learning with Convolutional Neural Networks Applied to Electromyography Data: A Resource for the Classification of Movements for Prosthetic Hands.
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A Prosthetic Hand Body Area Controller Based on Efficient Pattern Recognition Control Strategies.Surface EMG-Based Inter-Session Gesture Recognition Enhanced by Deep Domain Adaptation.Self-Recalibrating Surface EMG Pattern Recognition for Neuroprosthesis Control Based on Convolutional Neural Network.Comparison of six electromyography acquisition setups on hand movement classification tasks.Selectivity and Longevity of Peripheral-Nerve and Machine Interfaces: A Review.EMG-Based Estimation of Limb Movement Using Deep Learning With Recurrent Convolutional Neural Networks.Forearm Motion Recognition With Noncontact Capacitive SensingCauses of Performance Degradation in Non-invasive Electromyographic Pattern Recognition in Upper Limb ProsthesesReal-time, simultaneous myoelectric control using a convolutional neural networkMultiday EMG-Based Classification of Hand Motions with Deep Learning Techniques
P2860
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P2860
Deep Learning with Convolutional Neural Networks Applied to Electromyography Data: A Resource for the Classification of Movements for Prosthetic Hands.
description
2016 nî lūn-bûn
@nan
2016 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2016 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
name
Deep Learning with Convolution ...... ovements for Prosthetic Hands.
@ast
Deep Learning with Convolution ...... ovements for Prosthetic Hands.
@en
type
label
Deep Learning with Convolution ...... ovements for Prosthetic Hands.
@ast
Deep Learning with Convolution ...... ovements for Prosthetic Hands.
@en
prefLabel
Deep Learning with Convolution ...... ovements for Prosthetic Hands.
@ast
Deep Learning with Convolution ...... ovements for Prosthetic Hands.
@en
P2860
P921
P356
P1476
Deep Learning with Convolution ...... ovements for Prosthetic Hands.
@en
P2093
Henning Müller
Matteo Cognolato
P2860
P356
10.3389/FNBOT.2016.00009
P577
2016-09-07T00:00:00Z