Summary of defect detection algorithms based on deep learning
缺陷檢測是工業上非常重要的一個應用，由於缺陷多種多樣，傳統的機器視覺算法很難做到對缺陷特徵完整的建模和遷移，複用性不大，要求區分工況，這會浪費大量的人力成本。深度學習在特徵提取和定位上取得了非常好的效果，越來越多的學者和工程人員開始將深度學習算法引入到缺陷檢測領域中，下面將會介紹幾種深度學習算法在缺陷檢測領域中的應用。 Defect detection is a very important ap
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相關文章
- 1. Summary on deep learning framework --- TensorFlow
- 2. Summary on deep learning framework --- Torch7
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- 4. Summary on deep learning framework --- Theano && Lasagne
- 5. Summary on deep learning framework --- PyTorch
- 6. 對 Detection of Malicious Code Variants Based on Deep Learning 的簡單理解
- 7. 論文閱讀筆記《Segmentation-based deep-learning approach for surface-defect detection》
- 8. 論文閱讀筆記《Unsupervised fabric defect detection based on a deep convolutional GAN》
- 9. A Surface Defect Detection Method Based on Positive Samples
- 10. A Survey of Recommender Systems Based on Deep Learning （1）