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Zhuoxuan Fan

Shanxi Medical University · CN
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Area of research
Electrical and Electronic Engineering · Pulmonary and Respiratory Medicine
Research interest
Research topics from publications: YOLO-Weld: A Modified YOLOv5-Based Weld Feature Detection Network for Extreme Weld Noise. Representative work: Weld feature point detection is a key technology for welding trajectory planning and tracking. Existing two-stage detection methods and conventional convolutional neural network (CNN)-based approaches encounter performance bottlenecks under extreme welding noise conditions. To better obtain accurate weld feature point locations in high-noise environments, we propose a feature point detection network, YOLO-Weld, based on an improved You Only Look Once version 5 (YOLOv5). By introducing the reparameterized convolutional neural network (RepVGG) module, the network structure is optimized, enhancing detection speed. The utilization of a normalization-based attention module (NAM) in the network en
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Recent publications

YOLO-Weld: A Modified YOLOv5-Based Weld Feature Detection Network for Extreme Weld Noise
Sensors 2023cited by 21position: middledoi

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Frequent collaborators

Fuxin Du · Shandong University1 papers (2023–2023)Dongting Wu · Shandong University1 papers (2023–2023) · 1 papers (2023–2023) · 1 papers (2023–2023) · 1 papers (2023–2023)
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