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A Novel Hybrid Deep Learning Architecture for Dynamic Hand Gesture Recognition

DOI zum Zitieren der Version auf EPub Bayreuth: https://doi.org/10.15495/EPub_UBT_00008327
URN to cite this document: urn:nbn:de:bvb:703-epub-8327-8

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 der Verlagsversion: https://doi.org/10.1109/ACCESS.2024.3365274

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Further data

Item Type: Article in a journal
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
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
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
Language: English
Originates at UBT: Yes
URN: urn:nbn:de:bvb:703-epub-8327-8
Date Deposited: 20 Mar 2025 06:06
Last Modified: 20 Mar 2025 06:26
URI: https://epub.uni-bayreuth.de/id/eprint/8327
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