A one-stage approach for surface anomaly detection with background suppression strategies

Gaokai Liu, Ning Yang, Lei Guo, Shiping Guo, Zhi Chen

科研成果: 期刊稿件文章同行评审

17 引用 (Scopus)

摘要

We explore a one-stage method for surface anomaly detection in industrial scenarios. On one side, encoder-decoder segmentation network is constructed to capture small targets as much as possible, and then dual background suppression mechanisms are designed to reduce noise patterns in coarse and fine manners. On the other hand, a classification module without learning parameters is built to reduce information loss in small targets due to the inexistence of successive down-sampling processes. Experimental results demonstrate that our one-stage detector achieves state-of-the-art performance in terms of precision, recall and f-score.

源语言英语
文章编号1829
期刊Sensors
20
7
DOI
出版状态已出版 - 1 4月 2020

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