D-CenterNet: An Anchor-Free Detector With Knowledge Distillation for Industrial Defect Detection-Reference-Cited by-同舟云学术

D-CenterNet: An Anchor-Free Detector With Knowledge Distillation for Industrial Defect Detection

Published:2022 Issue: Volume:71 Page:1-12
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Liu Zhiwei¹^ORCID,Lyu Wentao¹^ORCID,Wang Chengqun¹^ORCID,Guo Qing²^ORCID,Zhou Di³^ORCID,Xu Weiqiang¹^ORCID

Affiliation:

1. School of Information Science and Engineering and the Key Laboratory of Intelligent Textile and Flexible Interconnection of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou, China

2. Zhejiang Technical Innovation Service Center, Hangzhou, China

3. Zhejiang UniView Technologies Company Ltd., Hangzhou, China

Funder

National Natural Science Foundation of China

State Key Laboratory of Synthetical Automation for Process Industries

Key Research and Development Program Foundation of Zhejiang

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/9717300/09877872.pdf?arnumber=9877872

Reference43 articles.

1. Deep Residual Learning for Image Recognition

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3. Relational Knowledge Distillation

4. Self-supervised Knowledge Distillation Using Singular Value Decomposition

5. Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer;zagoruyko;arXiv 1612 03928,2016

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