Intrinsic Dimension Estimation of Iudustrial Surface Defect Data and Its Impact on Classification

  • Jianbin Huang
  • , Wenheng Peng
  • , Junyuan Zheng
  • , Xiaopin Zhong
  • , Zong Ze Wu
  • , Weixiang Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In today's era of rapid development of artificial intelligence, machine vision technology based on deep learning is widely used. In this paper, the intrinsic dimension estimation of industrial defect data and its impact on classification and generalization are studied based on machine vision in the detection of industrial defects. In this work, Maximum Likelihood Estimation (MLE) algorithm is used to estimate the intrinsic dimensions of three common industrial defect data, and to verify the influence of the intrinsic dimensions on sample complexity and classification.

Original languageEnglish
Title of host publicationProceedings - 2023 China Automation Congress, CAC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7128-7132
Number of pages5
ISBN (Electronic)9798350303759
DOIs
StatePublished - 2023
Externally publishedYes
Event2023 China Automation Congress, CAC 2023 - Chongqing, China
Duration: 17 Nov 202319 Nov 2023

Publication series

NameProceedings - 2023 China Automation Congress, CAC 2023

Conference

Conference2023 China Automation Congress, CAC 2023
Country/TerritoryChina
CityChongqing
Period17/11/2319/11/23

Keywords

  • Classification
  • Intrinsic dimension
  • MLE
  • Sample complexity
  • Surface defect data

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