ZJU-Leaper: A Benchmark Dataset for Fabric Defect Detection and a Comparative Study-Reference-Cited by-同舟云学术

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ZJU-Leaper: A Benchmark Dataset for Fabric Defect Detection and a Comparative Study

Published:2020-12 Issue:3 Volume:1 Page:219-232
ISSN:2691-4581
Container-title:IEEE Transactions on Artificial Intelligence
language:
Short-container-title:IEEE Trans. Artif. Intell.

Author:

Zhang Chenkai^ORCID,Feng Shaozhe,Wang Xulongqi,Wang Yueming

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation of China

Zhejiang Lab

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9078688/9445210/09346038.pdf?arnumber=9346038

Cited by 25 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An approach to automatic fault detection in four-point system for knitted fabric with our benchmark dataset Isl-Knit;Heliyon;2024-09

2. Fabric defect detection based on feature enhancement and complementary neighboring information;Measurement Science and Technology;2024-07-18

3. Patterned Fabric Defect Detection Based on Separate Convolutional Unet;2024 International Conference on Data Science and Its Applications (ICoDSA);2024-07-10

4. A Novel Dataset for Fabric Defect Detection: Bridging Gaps in Anomaly Detection;Applied Sciences;2024-06-19

5. Autonomous AI-enabled Industrial Sorting Pipeline for Advanced Textile Recycling;2024 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT);2024-04-29

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