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A Novel Hybrid Deep Learning Architecture for Dynamic Hand Gesture Recognition

Title data

Hax, David Richard Tom ; Penava, Pascal ; Krodel, Samira ; Razova, Liliya ; Büttner, Ricardo:
A Novel Hybrid Deep Learning Architecture for Dynamic Hand Gesture Recognition.
In: IEEE Access. Vol. 12 (2024) . - pp. 28761-28774.
ISSN 2169-3536
DOI: https://doi.org/10.1109/ACCESS.2024.3365274

Official URL: Volltext

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Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Videos; Gesture recognition; Feature extraction; Computer architecture; Deep learning; Dynamics; Computational modeling; Human computer interaction; Convolutional neural networks; Recurrent neural networks; Long short term memory; Human-computer interaction; hand gesture recognition; video hand gesture; dynamic hand gesture; machine learning; deep learning; convolution neural networks; CNN; recurrent neural network; RNN; long-short-term memory; LSTM; inception model; inception-v3 architecture; hybrid architecture; feature extraction
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Former Professors > Chair Business Administration XVIII - Information Systems Management and Data Science - Univ.-Prof. Dr. Ricardo Büttner
Faculties
Faculties > Faculty of Law, Business and Economics
Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Former Professors
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 22 Mar 2025 22:00
Last Modified: 24 Mar 2025 06:16
URI: https://eref.uni-bayreuth.de/id/eprint/92925