An automatic and unsupervised image mask acquisition method based on generative adversarial networks

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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Bibliographic Details
Main Authors: Hao Wu, Yulong Liu, Jiankang Yang
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Systems Science & Control Engineering
Subjects:
Deep learning
defect detection
Mask R-CNN
Online Access:https://www.tandfonline.com/doi/10.1080/21642583.2023.2300835

Internet

https://www.tandfonline.com/doi/10.1080/21642583.2023.2300835

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