論文閱讀筆記《Supervised machine learning based surface inspection by synthetizing artificial defects》
核心思想 本文提出一種人工合成缺陷的方法，可用於表面缺陷檢測的數據集擴充。爲了解決缺陷檢測領域中，有缺陷樣本數量較少，無法對深度學習網絡進行充分訓練的問題，本文提出了一種人工合成缺陷的方法。整個合成流程主要包含四個步驟：1.生成骨架，2.紋理生成，3.對無缺陷圖像的修改，4.缺陷可視化程度的分析。 首先，採用一種隨機遊走的方式來生成一個二維的缺陷圖像骨架或者說輪廓，從圖中的一個隨機座標點出
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相關文章
- 1. Machine Learning & Deep Learning 論文閱讀筆記
- 2. 論文閱讀筆記《Segmentation-based deep-learning approach for surface-defect detection》
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- 4. 論文閱讀：Dual Supervised Learning
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