Multi-class classification method using twin support vector machines with multi-information for steel surface defects-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Multi-class classification method using twin support vector machines with multi-information for steel surface defects

Published:2018-05 Issue: Volume:176 Page:108-118
ISSN:0169-7439
Container-title:Chemometrics and Intelligent Laboratory Systems
language:en
Short-container-title:Chemometrics and Intelligent Laboratory Systems

Author:

Chu Maoxiang,Liu Xiaoping,Gong Rongfen,Liu Liming

Funder

Liaoning Province

Liaoning Province Ministry of Education

HIT

University of Science and Technology Liaoning Foundation

Publisher

Elsevier BV

Subject

Spectroscopy,Process Chemistry and Technology,Computer Science Applications,Software,Analytical Chemistry

Reference32 articles.

1. A cost-effective and automatic surface defect inspection system for hot-rolled flat steel;Luo;Robot. Comput. Integrated Manuf.,2016

2. Vision-based automatic detection of steel surface defects in the cold rolling process: considering the influence of industrial liquids and surface textures;Zhao;Int. J. Adv. Manuf. Technol.,2017

3. Classification of steel samples by laser-induced breakdown spectroscopy and random forest;Zhang;Chemometr. Intell. Lab. Syst.,2016

4. A fast detection method for region of defect on strip steel surface;Gong;ISIJ Int.,2015

5. A local annular contrast based real-time inspection algorithm for steel bar surface defects;Li;Appl. Surf. Sci.,2012

Cited by 36 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 efficient steel defect detection model based on multi-scale information extraction;Robotic Intelligence and Automation;2024-08-13

2. SCFNet: Lightweight Steel Defect Detection Network Based on Spatial Channel Reorganization and Weighted Jump Fusion;Processes;2024-05-02

3. Steel surface defect detection algorithm based on ESI-YOLOv8;Materials Research Express;2024-05-01

4. A Survey of Vision-Based Methods for Surface Defects’ Detection and Classification in Steel Products;Informatics;2024-04-23

5. Detection of Manufacturing Defects in Steel Using Deep Learning With Explainable Artificial Intelligence;IEEE Access;2024

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3