Intelligent monitoring of small target detection using YOLOv8
In complex scenes, small target face detection is crucial but often hampered by detection accuracy and efficiency limitations. Our method addresses these challenges by incorporating Gaussian noise, which is key in improving model robustness and generalization. By simulating real-world imperfections,...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Alexandria Engineering Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016824012791 |
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| author | Lei Sun Yang Shen |
| author_facet | Lei Sun Yang Shen |
| author_sort | Lei Sun |
| collection | DOAJ |
| description | In complex scenes, small target face detection is crucial but often hampered by detection accuracy and efficiency limitations. Our method addresses these challenges by incorporating Gaussian noise, which is key in improving model robustness and generalization. By simulating real-world imperfections, Gaussian noise acts as a regularizer and makes the model more resistant to variations in lighting and texture. Traditional methods often face difficulties when dealing with small targets and complex backgrounds due to inadequate feature extraction, suboptimal loss function design, and vulnerability to noise. To overcome these issues, we propose an improved YOLOv8 model based on multi-scale feature fusion and an optimized loss function. By leveraging Gaussian noise during training, our approach enhances both detection accuracy and operating efficiency. Experiments on the FDDB and WIDER FACE datasets demonstrate that our method performs better in various complex scenarios. Our method achieved 0.780 on the WIDER FACE validation set, outperforming existing mainstream techniques. |
| format | Article |
| id | doaj-art-7dc6fa7657d840fc8b43183af90a9c24 |
| institution | Kabale University |
| issn | 1110-0168 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj-art-7dc6fa7657d840fc8b43183af90a9c242025-01-29T05:00:15ZengElsevierAlexandria Engineering Journal1110-01682025-01-01112701710Intelligent monitoring of small target detection using YOLOv8Lei Sun0Yang Shen1School of Information Engineering, Suqian University, Suqian, 223800, China; Corresponding author.Industrial Technology Research Institute of Suqian University, Suqian, 223800, ChinaIn complex scenes, small target face detection is crucial but often hampered by detection accuracy and efficiency limitations. Our method addresses these challenges by incorporating Gaussian noise, which is key in improving model robustness and generalization. By simulating real-world imperfections, Gaussian noise acts as a regularizer and makes the model more resistant to variations in lighting and texture. Traditional methods often face difficulties when dealing with small targets and complex backgrounds due to inadequate feature extraction, suboptimal loss function design, and vulnerability to noise. To overcome these issues, we propose an improved YOLOv8 model based on multi-scale feature fusion and an optimized loss function. By leveraging Gaussian noise during training, our approach enhances both detection accuracy and operating efficiency. Experiments on the FDDB and WIDER FACE datasets demonstrate that our method performs better in various complex scenarios. Our method achieved 0.780 on the WIDER FACE validation set, outperforming existing mainstream techniques.http://www.sciencedirect.com/science/article/pii/S1110016824012791Face detectionMulti-scale feature fusionYOLOv8Low-level vision |
| spellingShingle | Lei Sun Yang Shen Intelligent monitoring of small target detection using YOLOv8 Alexandria Engineering Journal Face detection Multi-scale feature fusion YOLOv8 Low-level vision |
| title | Intelligent monitoring of small target detection using YOLOv8 |
| title_full | Intelligent monitoring of small target detection using YOLOv8 |
| title_fullStr | Intelligent monitoring of small target detection using YOLOv8 |
| title_full_unstemmed | Intelligent monitoring of small target detection using YOLOv8 |
| title_short | Intelligent monitoring of small target detection using YOLOv8 |
| title_sort | intelligent monitoring of small target detection using yolov8 |
| topic | Face detection Multi-scale feature fusion YOLOv8 Low-level vision |
| url | http://www.sciencedirect.com/science/article/pii/S1110016824012791 |
| work_keys_str_mv | AT leisun intelligentmonitoringofsmalltargetdetectionusingyolov8 AT yangshen intelligentmonitoringofsmalltargetdetectionusingyolov8 |