AI-Based Image Processing Detection and Classification Analysis for Multidisciplinary Approaches: Second Edition

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 20 January 2027 | Viewed by 688

Editor

Special Issue Information

Dear Colleagues,

We are pleased to announce the second volume of this Special Issue of Electronics, “AI-Based Image Processing Detection and Classification Analysis for Multidisciplinary Approaches: Second Edition”, following its prior success. This Special Issue explores cutting-edge advancements in AI-based detection and classification analysis within the realm of image processing. Covering multidisciplinary approaches, this Special Issue delves into the theoretical foundations and practical applications of AI technologies in various fields. From medical imaging to remote sensing and beyond, researchers and practitioners contribute their insights, methodologies, and case studies to elucidate the transformative impact of AI on image-processing techniques. This Special Issue aims to provide a comprehensive overview of the state-of-the-art methods, challenges, and future directions in leveraging AI for enhancing image detection and classification across diverse domains.

This Special Issue explores the theoretical underpinnings and practical applications of AI methodologies, including machine learning, deep learning, and computer vision, in addressing complex challenges in image analysis. Contributions cover a wide range of multidisciplinary domains, including medical imaging, satellite imagery, surveillance, and industrial automation. Through this collection of research articles, this Special Issue provides valuable insights into the theory and practical implementation of AI-driven solutions for image processing across diverse fields.

Artificial intelligence (AI) and image processing techniques have revolutionized the field of detection and classification analysis across various disciplines. The integration of AI algorithms with image processing methods enables the automated analysis of complex data, leading to advancements in multidisciplinary approaches. This Special Issue aims to explore the theoretical foundations and practical applications of AI-based image processing for detection and classification analysis in multidisciplinary contexts.

We welcome submissions on topics related to new theories and evolutionary methods for AI-based image processing detection, and classification analysis across multidisciplinary applications. A non-exhaustive list of topics is as follows:

  • Medical image analysis;
  • Feature selection, extraction, and learning;
  • Remote sensing and earth observation;
  • Object detection and recognition;
  • Biometric recognition;
  • Image restoration and noise reduction;
  • Industrial quality control and inspection;
  • Environmental monitoring and conservation;
  • Forensic imaging and analysis;
  • Use of image transforms and moments in enhancement analysis;
  • Art and cultural heritage preservation;
  • Human activity recognition and behavior analysis;
  • Ethical and societal implications of AI in image processing.

Dr. Honarvar Shakibaei Asli
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • image processing detection
  • image analysis
  • artificial intelligence

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Review

51 pages, 5501 KB  
Review
State of the Art in AI-Based Visual Inspection for Industrial Quality Control: Methods, Benchmarks, Challenges, and Autonomous Systems
by Amal Jayawardena, Jung-Hoon Sul, Diluka Moratuwage, Jaliya L. Wijayaraja and Lasitha Piyathilaka
Electronics 2026, 15(12), 2727; https://doi.org/10.3390/electronics15122727 - 20 Jun 2026
Viewed by 553
Abstract
Industrial quality control is a critical component of modern manufacturing, as defects can lead to significant economic losses and safety risks. Traditional inspection methods, largely reliant on human operators or rule-based systems, often suffer from inconsistency, limited scalability, and reduced accuracy in complex [...] Read more.
Industrial quality control is a critical component of modern manufacturing, as defects can lead to significant economic losses and safety risks. Traditional inspection methods, largely reliant on human operators or rule-based systems, often suffer from inconsistency, limited scalability, and reduced accuracy in complex environments. Recent advances in artificial intelligence (AI), particularly in deep learning and computer vision, have enabled automated defect detection and classification with unprecedented performance. This paper provides a comprehensive review of AI-based image processing techniques for industrial quality control, covering classification, detection, and segmentation approaches. Key applications across manufacturing sectors are discussed, alongside current challenges such as data scarcity, real-time implementation, and model generalisation. Furthermore, this paper explores emerging trends toward autonomous inspection systems, integrating real-time analytics, edge computing, and intelligent decision making. The insights presented aim to guide future research toward robust, scalable, and fully automated quality control solutions in smart manufacturing environments. Full article
Show Figures

Figure 1

Back to TopTop