DualCascadeTSF-MobileNetV2: A Lightweight Violence Behavior Recognition Model
This paper proposes a lightweight violent behavior recognition model, DualCascadeTSF-MobileNetV2, which is improved based on the temporal shift module and its subsequent research. By introducing the Dual Cascade Temporal Shift and Fusion module, the model further enhances the feature correlation abi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-04-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/7/3862 |
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| author | Yuang Chen Yong Li Shaohua Li Shuhan Lv Fang Lin |
| author_facet | Yuang Chen Yong Li Shaohua Li Shuhan Lv Fang Lin |
| author_sort | Yuang Chen |
| collection | DOAJ |
| description | This paper proposes a lightweight violent behavior recognition model, DualCascadeTSF-MobileNetV2, which is improved based on the temporal shift module and its subsequent research. By introducing the Dual Cascade Temporal Shift and Fusion module, the model further enhances the feature correlation ability in the time dimension and solves the problem of information sparsity caused by multiple temporal shifts. Meanwhile, the model incorporates the efficient lightweight structure of MobileNetV2, significantly reducing the number of parameters and computational complexity. Experiments were conducted on three public violent behavior datasets, Crowd Violence, RWF-2000, and Hockey Fights, to verify the performance of the model. The results show that it outperforms other classic models in terms of accuracy, computational speed, and memory size, especially among lightweight models. This research continues and expands on the previous achievements in the fields of TSM and lightweight network design, providing a new solution for real-time violent behavior recognition on edge devices. |
| format | Article |
| id | doaj-art-47e4b1cbed9e431985282d8b7242cd68 |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-47e4b1cbed9e431985282d8b7242cd682025-08-20T02:09:14ZengMDPI AGApplied Sciences2076-34172025-04-01157386210.3390/app15073862DualCascadeTSF-MobileNetV2: A Lightweight Violence Behavior Recognition ModelYuang Chen0Yong Li1Shaohua Li2Shuhan Lv3Fang Lin4Key Laboratory of CTC & IE (Engineering University of PAP), Ministry of Education, Engineering University of PAP, Xi’an 710086, ChinaKey Laboratory of CTC & IE (Engineering University of PAP), Ministry of Education, Engineering University of PAP, Xi’an 710086, ChinaKey Laboratory of CTC & IE (Engineering University of PAP), Ministry of Education, Engineering University of PAP, Xi’an 710086, ChinaKey Laboratory of CTC & IE (Engineering University of PAP), Ministry of Education, Engineering University of PAP, Xi’an 710086, ChinaKey Laboratory of CTC & IE (Engineering University of PAP), Ministry of Education, Engineering University of PAP, Xi’an 710086, ChinaThis paper proposes a lightweight violent behavior recognition model, DualCascadeTSF-MobileNetV2, which is improved based on the temporal shift module and its subsequent research. By introducing the Dual Cascade Temporal Shift and Fusion module, the model further enhances the feature correlation ability in the time dimension and solves the problem of information sparsity caused by multiple temporal shifts. Meanwhile, the model incorporates the efficient lightweight structure of MobileNetV2, significantly reducing the number of parameters and computational complexity. Experiments were conducted on three public violent behavior datasets, Crowd Violence, RWF-2000, and Hockey Fights, to verify the performance of the model. The results show that it outperforms other classic models in terms of accuracy, computational speed, and memory size, especially among lightweight models. This research continues and expands on the previous achievements in the fields of TSM and lightweight network design, providing a new solution for real-time violent behavior recognition on edge devices.https://www.mdpi.com/2076-3417/15/7/3862deep learninglightweight modelsviolence behavior recognitionedge devices |
| spellingShingle | Yuang Chen Yong Li Shaohua Li Shuhan Lv Fang Lin DualCascadeTSF-MobileNetV2: A Lightweight Violence Behavior Recognition Model Applied Sciences deep learning lightweight models violence behavior recognition edge devices |
| title | DualCascadeTSF-MobileNetV2: A Lightweight Violence Behavior Recognition Model |
| title_full | DualCascadeTSF-MobileNetV2: A Lightweight Violence Behavior Recognition Model |
| title_fullStr | DualCascadeTSF-MobileNetV2: A Lightweight Violence Behavior Recognition Model |
| title_full_unstemmed | DualCascadeTSF-MobileNetV2: A Lightweight Violence Behavior Recognition Model |
| title_short | DualCascadeTSF-MobileNetV2: A Lightweight Violence Behavior Recognition Model |
| title_sort | dualcascadetsf mobilenetv2 a lightweight violence behavior recognition model |
| topic | deep learning lightweight models violence behavior recognition edge devices |
| url | https://www.mdpi.com/2076-3417/15/7/3862 |
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