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About Automatic Detection of Welding Defects Using Deep PDF
The document summarizes a research paper that proposes using a deep neural network for automatic detection of welding defects from x-ray images. Specifically, it uses sparse auto-encoders to perform unsupervised feature learning from image patches, without needing to manually extract features. A softmax regression layer is then added for supervised classification. Experimental results showed the deep learning model was effective at detecting welding defects in x-ray images.
Detailed Information
| Author: | ['ahmad'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 11 |
| Language: | English |
| Format: | |
| Price: | FREE |
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