基于改进YOLOv3的印刷电路板缺陷检测算法
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卞佰成,陈田,吴入军,刘军
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Improved YOLOv3-based defect detection algorithm for printed circuit board
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Bai-cheng BIAN,Tian CHEN,Ru-jun WU,Jun LIU
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| 表 1 不同主干网络参数的对比 |
| Tab.1 Comparison of different backbone network parameters |
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| 主干网络模型 | 输入图像分辨率/像素 | 感受野分辨率/像素 | NP/106 | GFLOPs | ti/ms | | DarkNet53 | 416×416 | 725×725 | 40.603 | 49.2 | 13 | | ResNet50 | 416×416 | 483×483 | 23.508 | 28.3 | 10.9 | | ResNet101 | 416×416 | 1027×1027 | 42.5 | 54.0 | 21.7 | | ResNeSt50 | 416×416 | 543×543 | 25.434 | 37.2 | 17 | | ResNeSt101 | 416×416 | 1119×1119 | 46.226 | 70.6 | 27 |
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