Context-Aware Adaptive Weighted Attention Network for Real-Time Surface Defect Segmentation-Reference-Cited by-同舟云学术

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Context-Aware Adaptive Weighted Attention Network for Real-Time Surface Defect Segmentation

Published:2024 Issue: Volume:73 Page:1-13
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Zhang Gaowei¹^ORCID,Lu Yang¹^ORCID,Jiang Xiaoheng¹^ORCID,Yan Feng¹^ORCID,Xu Mingliang¹^ORCID

Affiliation:

1. School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Natural Science Foundation of Henan Province

CAAI-Huawei MindSpore OpenFund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/19/10367905/10648860.pdf?arnumber=10648860

Reference59 articles.

1. An End-to-End Steel Surface Defect Detection Approach via Fusing Multiple Hierarchical Features

2. A fast and robust convolutional neural network-based defect detection model in product quality control

3. ES-Net: Efficient Scale-Aware Network for Tiny Defect Detection

4. Classification of Surface Defects Based on Improved Gabor Filter

5. Surface Defect Modelling Using Co-occurrence Matrix and Fast Fourier Transformation

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