論文閱讀筆記《Automatic Fabric Defect Detection with a Multi-Scale Convolutional Denoising Autoencoder Net》
核心思想 本文提出一種多尺度卷積去噪自動編碼器網絡（MSCDAE）實現了對布匹紡織物缺陷的無監督檢測，算法的思路其實並不複雜，作者使用正樣本對卷積自動編碼器（CAE）進行訓練，使得其具備提取織物特徵並重構織物圖像的能力。當帶有缺陷的樣本輸入到網絡中時，由於缺陷處的特徵與正常織物的特徵不同，因此CAE並不能夠重構缺陷處的圖像，重構後的圖像缺陷處將將重構後的圖像與原始圖像做差，缺陷處的差異會明顯大
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相關文章
- 1. 論文閱讀筆記《Unsupervised fabric defect detection based on a deep convolutional GAN》
- 2. 論文閱讀筆記《Automatic Metallic Surface Defect Detection and Recognition with Convolutional Neural Networ》
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- 9. 論文閱讀筆記《Segmentation-based deep-learning approach for surface-defect detection》
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