EMO-MoviNet: Enhancing Action Recognition in Videos with EvoNorm, Mish Activation, and Optimal Frame Selection for Efficient Mobile Deployment

The primary goal of this study is to develop a deep neural network for action recognition that enhances accuracy and minimizes computational costs. In this regard, we propose a modified EMO-MoviNet-A2* architecture that integrates Evolving Normalization (EvoNorm), Mish activation, and optimal frame...

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Detalles Bibliográficos
Autores principales: Hussain, Tarique, Memon, Zulfiqar Ali, Qureshi, Rizwan, Alam, Tanvir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10574851/
https://www.ncbi.nlm.nih.gov/pubmed/37836936
http://dx.doi.org/10.3390/s23198106

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10574851/
https://www.ncbi.nlm.nih.gov/pubmed/37836936
http://dx.doi.org/10.3390/s23198106

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