A Hand-Modeled Feature Extraction-Based Learning Network to Detect Grasps Using sEMG Signal

A Hand-Modeled Feature Extraction-Based Learning Network to Detect Grasps Using sEMG Signal

Recently, deep models have been very popular because they achieve excellent performance with many classification problems. Deep networks have high computational complexities and require specific hardware. To overcome this problem (without decreasing classification ability), a hand-modeled feature se...

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Bibliographic Details
Main Authors: Mehmet Baygin, Prabal Datta Barua, Sengul Dogan, Turker Tuncer, Sefa Key, U. Rajendra Acharya, Kang Hao Cheong
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Sensors
Subjects:
frustum pattern
Frustum154
sEMG signal classification
grasp detection
Online Access:https://www.mdpi.com/1424-8220/22/5/2007

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https://www.mdpi.com/1424-8220/22/5/2007

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