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Deep learning for electromyographic hand gesture signal classification using transfer learning

Résumé

In recent years, deep learning algorithms have become increasingly more prominent for their unparalleled ability to automatically learn discriminant features from large amounts of data. However, within the field of electromyography-based gesture recognition, deep learning algorithms are seldom employed as they require an unreasonable amount of effort from a single person, to generate tens of thousands of examples.

Publication
Transactions on Neural Systems and Rehabilitation Engineering (IEEE NSRE)
Alexandre Drouin
Alexandre Drouin
Head of AI Frontier Research​

Head of AI Frontier Research​ at AI Frontier Research located at Montreal, QC, Canada.