A Novel Hybrid Deep Learning Architecture for Dynamic Hand Gesture Recognition

Hand gestures are a form of natural communication used in human-computer interaction, however, when gestures are video-based, extraction of features for classification is complex. Current machine learning models struggle to achieve high accuracies when using videos recorded in realistic environments...

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主要な著者:	David Richard Tom Hax, Pascal Penava, Samira Krodel, Liliya Razova, Ricardo Buettner
フォーマット:	Artigo
言語:	Inglês
出版事項:	IEEE 2024-01-01
シリーズ:	IEEE Access
主題:	Human-computer interaction hand gesture recognition video hand gesture dynamic hand gesture machine learning deep learning
オンライン･アクセス:	https://ieeexplore.ieee.org/document/10433143/
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