Algorithms and Computational Methods for Industrial Vision and Intelligent Inspection

Dear Colleagues,

The rapid evolution of Industry 4.0 and smart manufacturing has placed industrial vision and intelligent inspection at the forefront of technological innovation. Driven by advancements in artificial intelligence (AI), particularly deep learning, computer vision algorithms now enable unprecedented accuracy in defect detection, dimensional measurement, surface analysis, and process monitoring across industries, such as automotive, electronics, semiconductors, pharmaceuticals, and heavy machinery. However, the unique challenges of industrial environments, including real-time processing requirements, limited annotated data, and harsh operating conditions, demand specialized algorithmic innovations and computational methods tailored to these constraints.

This Special Issue aims to showcase cutting-edge research at the intersection of algorithms, computational methods, and industrial vision/intelligent inspection. We invite submissions that advance both theoretical foundations and practical applications, with a focus on addressing the unique challenges of different inspection scenes, such as high-speed processing, limited labeled data, harsh operating conditions, and stringent accuracy requirements. Topics of interest include, but are not limited to, the following:

• Defect detection and classification;
• Computational methods for industrial 3D vision;
• Multimodal fusion in industrial scenarios;
• Small-data and few-shot learning techniques for industrial scenarios;
• Real-time edge computing ;
• Anomaly detection for unknown defect identification;
• Vision-language models for industrial scenarios;
• Synthetic data generation and domain adaptation;
• Explainable AI for industrial trust.

In addition, beyond traditional manufacturing, intelligent inspection is rapidly expanding into various high-value and technically demanding sectors. We also encourage submissions discussing typical applications of intelligent inspection in other fields:

• Energy and power;
• Aerospace and high-end equipment ;
• Semiconductor and electronics manufacturing;
• Infrastructure and smart cities;
• Textiles and advanced materials;
• Automotive and transportation equipment.

We welcome original research articles, comprehensive reviews, and case studies that demonstrate tangible impact in different inspection scenes. All papers will undergo rigorous peer review to ensure scientific rigor and relevance to the field.

Dr. Lei Yang
Dr. Junfeng Fan
Dr. Yunkai Ma
Prof. Dr. En Li
Guest Editors

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. Mathematics 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 2600 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.

• artificial intelligence
• deep learning
• industrial vision
• intelligent inspection
• defect detection
• anomaly detection
• real-time processing
• few-shot learning
• 3D vision
• image segmentation
• computer vision