基于多尺度密集对比增强自监督的简统化接触网缺陷检测

针对简统化接触网缺陷检测缺陷样本少、目标小、类别多的问题,提出基于多尺度密集对比增强自监督的简统化接触网缺陷检测方法。利用编码器提取多尺度特征,构建多尺度对比和密集对比更新模型,通过迁移学习的方式获取预训练模型,进而获得高精度缺陷检测模型。实验证明本文所述方法具有一定的可行性和有效性,对于研发可实际应用的简统化接触网缺陷检测系统具有重要意义。

With regard to the problems of few samples,minor targets and many categories of defects of simplified and unified OCL for inspection.The paper proposes a simplified and unified OCL defect inspection method based on multi-scale dense contrast enhanced self-monitoring.The encoder is used to extract multi-scale features,build multi-scale contrast and intensive contrast update models,and obtain pre-training models through transfer learning,thus obtaining high-precision defect inspection models.The experiment proves that the method described in the paper is feasible and effective,and it is of great significance for the development of a practical simplified and unified OCL defect inspection system.