The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Surface Defect Saliency of Magnetic Tile
Abstract
Vision-based detection on surface defects has long postulated in the magnetic tile automation process. In this work, we introduce a real-time and multi-module neural network model called MCuePush U-Net, specifically designed for the image saliency detection of magnetic tile. We show that the model exceeds the state-of-the-art, in which it both effectively and explicitly maps multiple surface defects from low-contrast images. Our model significantly reduces time cost of machinery from 0.5s per image to 0.07s, and enhances saliency accuracy on surface defect detection.
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“Many of them are limited to the inspection of textured surfaces or focus on novelty detection in multi-class semantic segmentation scenarios.”
From The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection (2021) · cites this paper as Huang et al. (2018)
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Metadata
- Authors
- Huang, Y., Qiu, C., Guo, Y., Wang, X., & Yuan, K.
- Affiliations
- Chinese Academy of Sciences (CN)
- Columbia University (US)
- Venue
- 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)
- Publisher
- IEEE
- Published
- 2018-08
- Pages
- 612-617
- ISSN
- 2161-8070 (ISSN-L)
- OpenAlex
- W2905065306
- Cited by
- 117
- References
- 36
- Citations by year
- 2026: 10 · 2025: 21 · 2024: 12 · 2023: 24 · 2022: 23 · 2021: 17 · 2020: 7 · 2019: 3
- FWCI
- 10.63
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Conference on Automation Science and Engineering (CASE) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Industrial Vision Systems and Defect Detection
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Keywords
- surface defect detection, magnetic tiles, image saliency, U-Net, real-time defect detection, low-contrast images
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