Surface Defect Detection Using Deep Learning: A Comprehensive Investigation and Emerging Trends

Fajar Pitarsi Dharma, Moses Laksono Singgih*

*Corresponding author for this work

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

Abstract

Surface defect detection is currently a topic that contributes important things in identifying and assessing defects based on surface appearances, finding widespread applications in diverse manufacturing industries. This approach involves the effective handling and analysis of surface appearances using image processing techniques, coupled with the utilization of deep learning methods for defect detection in several materials such as fabric, steel, aluminum, welding, and others. However, the existing research in this field is confronted with several limitations pertaining to the accuracy, speed, and balance of defect detection outcomes. In response to these challenges, this research paper presents a comprehensive investigation into deep learning techniques for surface defect detection in some applications in industries. With the growing demand for efficient and accurate defect detection in various industries, this study aims to explore the current state of research, identify key research gaps, and shed light on the emerging trends in leveraging deep learning for surface defect detection. Through a meticulous review investigation of relevant literature and an in-depth analysis of existing studies, this research provides valuable insights into the advancements, challenges, and potential future directions in this topic area.

Original languageEnglish
Title of host publicationAI Technologies and Virtual Reality - Proceedings of 7th International Conference on Artificial Intelligence and Virtual Reality AIVR 2023
EditorsKazumi Nakamatsu, Srikanta Patnaik, Roumen Kountchev
PublisherSpringer Science and Business Media Deutschland GmbH
Pages247-260
Number of pages14
ISBN (Print)9789819990177
DOIs
Publication statusPublished - 2024
Event7th International Conference on Artificial Intelligence and Virtual Reality, AIVR 2023 - Kumamoto, Japan
Duration: 21 Jul 202323 Jul 2023

Publication series

NameSmart Innovation, Systems and Technologies
Volume382
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Conference

Conference7th International Conference on Artificial Intelligence and Virtual Reality, AIVR 2023
Country/TerritoryJapan
CityKumamoto
Period21/07/2323/07/23

Keywords

  • Deep learning
  • Emerging trends
  • Image processing
  • Manufacturing industries
  • Research gaps
  • Surface defect detection

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