An automatic and unsupervised image mask acquisition method based on generative adversarial networks
This paper proposes an unsupervised method for automatically labelling and obtaining image masks in defect detection. Since it is very labour intensive to acquire the image masks needed for deep learning (e.g. in semantic segmentation tasks) via manual labelling, we propose a method that utilize a g...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
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| Series: | Systems Science & Control Engineering |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/21642583.2023.2300835 |
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