基于图像融合技术与改进Faster R-CNN的绝缘子故障识别
为提高地铁接触网绝缘子故障检测精度,文中提出一种融合双流注意力生成对抗网络(DSAGAN)与改进Faster R-CNN的检测框架。针对多源图像特征融合难题,通过DSAGAN实现接触网绝缘子红外与可见光图像的高效融合:生成器采用注意力机制强化关键特征提取,判别器引入最小二乘损失函数替代传统交叉熵,有效保留纹理细节并提升网络稳定性。在故障识别阶段,改进Faster R-CNN模型采用ResNet101替代VGG16作为主干网络,结合残差连接缓解梯度异常问题,并在RPN层嵌入非极大值抑制(NMS ...
耿占权, 苏飞
doaj
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