High-performance one-stage detector for SiC crystal defects based on convolutional neural network-Reference-Cited by-同舟云学术

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High-performance one-stage detector for SiC crystal defects based on convolutional neural network

Published:2023-11 Issue: Volume:280 Page:110994
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Shi Haochen,Jin Zhiyuan,Tang Wenjing,Wang Jing,Jiang Kai,Xu Mingsheng,Xia Wei,Xu Xiangang

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference40 articles.

1. SiC sensors: a review;Wright;J. Phys. D,2007

2. Formation of extended defects in 4H-SiC epitaxial growth and development of a fast growth technique;Tsuchida;Phys. Status Solidi.,2009

3. Soft matching network with application to defect inspection;Zhang;Knowl.-Based Syst.,2021

4. A noise robust method based on completed local binary patterns for hot-rolled steel strip surface defects;Song;Appl. Surf. Sci.,2013

5. AdaBoost learning for fabric defect detection based on HOG and SVM;Shumin,2011

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1. LiFSO-Net: A lightweight feature screening optimization network for complex-scale flat metal defect detection;Knowledge-Based Systems;2024-09

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