A Novel Human Action Recognition Model by Grad-CAM Visualization with Multi-level Feature Extraction Using Global Average Pooling with Sequence Modeling by Bidirectional Gated Recurrent Units
Abstract Human action recognition is essential in many real-world scenarios, such as video surveillance, human–computer interaction, and behavior analysis. Despite the progress in deep learning, issues such as occlusion, distraction from the background, and motion pattern variability still exist, th...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-05-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44196-025-00848-x |
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