論文閱讀筆記《Convolutional Neural Networks for Steel Surface Defect Detection from Photometric Stereo》
小樣本學習&元學習經典論文整理||持續更新 核心思想 本文提出一種使用光度立體圖像（Photometric Stereo Images）對鋼軌表面缺陷進行檢測的方法，關於光度立體圖像我沒找到特別詳細的介紹，大體的概念是被拍攝的物體保持不動，光源會移動到多個位置，分別拍攝照片。根據圖像中高光部分和陰影部分的變化，來獲取物體的3D信息。但本文構建的圖像採集裝置似乎不是這樣實現的，該裝置的示意圖如下
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相關文章
- 1. 論文閱讀筆記《A High-Efficiency Fully Convolutional Networks for Pixel-Wise Surface Defect Detection》
- 2. 論文閱讀筆記《Automatic Metallic Surface Defect Detection and Recognition with Convolutional Neural Networ》
- 3. 論文閱讀筆記《Segmentation-based deep-learning approach for surface-defect detection》
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