A Coarse and Fine Grained Network for Industrial Surface Defect Classification
Author:
Affiliation:
1. Shanghai Development Center of Computer Software Technology, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3663976.3664011
Reference17 articles.
1. The Performance Analysis of Transfer Learning for Steel Defect Detection by Using Deep Learning
2. FDD: a deep learning–based steel defect detectors
3. An effective industrial defect classification method under the few-shot setting via two-stream training
4. Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, 2020. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020).
5. IndusSynthe: Synthetic data using human-machine intelligence hybrid for enhanced industrial surface defect detection through self-updating with multi-view filtering
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