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A forest fire identification and monitoring model based on improved YOLOv8. [PDF]
Sci RepZheng Y, Guo P, Tian X, Ye Y.
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YOLOv8-LC9: a modified YOLOv8 for weld surface detection
Engineering Research ExpressAbstract In order to address the computational resource constraints experienced in weld inspection equipment, this study proposes YOLOv8-LC9, a lightweight real-time detection model. The model is built upon ResNet, integrating depthwise, group, and pointwise convolutions to construct lightweight feature extraction modules (C9 and C3Ghost)
Zhaokai Sun, Zemin Feng, Ming Zhang
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MBE-YOLOv8: enhancing building crack detection with an advanced YOLOv8 framework
Measurement Science and TechnologyAbstract Buildings, over prolonged periods, are susceptible to developing various types of cracks, which are often small and exhibit low contrast, leading to challenges in accurate detection. Missed detections and false positives due to these characteristics can result in delayed repairs, thereby compromising structural integrity and ...
Zhen Zhang +4 more
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YOLOv8-AMCD: Improved YOLOv8 for Small Object Detection
2024 6th International Conference on Robotics and Computer Vision (ICRCV)YuYing Liang, Xin Chen
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DL-YOLOv8: Improved YOLOv8 for Cable Sheath Defect Detection
2024 The 9th International Conference on Power and Renewable Energy (ICPRE)Xiao Xu +5 more
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YOLOv8-GR: Gesture Recognition by Improving of YOLOv8 Algorithm
2024 Twelfth International Conference on Advanced Cloud and Big Data (CBD)Yi Ding, Naixuan Guo, Haitao Meng
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CoT-YOLOv8: Improved YOLOv8 for Aerial images Small Target Detection
2023 China Automation Congress (CAC), 2023Yuhe Wang +4 more
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