Rain-Like Layer Removal From Hot-Rolled Steel Strip Based on Attentive Dual Residual Generative Adversarial Network-Reference-Cited by-同舟云学术

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Rain-Like Layer Removal From Hot-Rolled Steel Strip Based on Attentive Dual Residual Generative Adversarial Network

Published:2023 Issue: Volume:72 Page:1-15
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Luo Qiwu¹^ORCID,He Handong¹^ORCID,Liu Kexin¹^ORCID,Yang Chunhua¹^ORCID,Silvén Olli²^ORCID,Liu Li³^ORCID

Affiliation:

1. School of Automation, Central South University, Changsha, China

2. Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Oulu, Finland

3. College of Electronic Science, National University of Defense Technology, Changsha, China

Funder

National Natural Science Foundation of China

Hunan Provincial Natural Science Foundation of China

Science and Technology Innovation Program of Hunan Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10098150.pdf?arnumber=10098150

Reference51 articles.

1. Semi-supervised defect classification of steel surface based on multi-training and generative adversarial network

2. Surface Defect Classification for Hot-Rolled Steel Strips by Selectively Dominant Local Binary Patterns

3. Saliency Optimization from Robust Background Detection

4. Salient Object Detection via Multiple Instance Learning

5. Automated Visual Defect Classification for Flat Steel Surface: A Survey

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