Mathematical Methods in Machine Learning, Neural Networks and Computer Vision
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: 31 January 2026 | Viewed by 1018
Special Issue Editor
Interests: pattern recognition; human activity recognition; face recognition; image processing; big data analytics; machine learning; biomechanics and health; computational finance; high-performance computing; wireless sensor networks; wearable devices; applied electromagnetics; antennas; radiowave propagation and wireless communications; high-power microwave; pulsed power and plasma science; engineering education
Special Issue Information
Dear Colleagues,
This Special Issue, entitled "Mathematical Methods in Machine Learning, Neural Networks and Computer Vision", aims to explore the intersection of advanced mathematical techniques with cutting-edge applications in artificial intelligence. It encompasses research into mathematical tools, novel algorithms, optimization strategies, and theoretical frameworks that underpin the development and enhancement of machine learning models, neural networks, and computer vision systems. Contributions to this Special Issue include studies on statistical learning theories, deep learning architectures, computational geometry, graph-based methods, and their applications in time series analysis, image recognition, video processing, natural language processing, and autonomous systems. This Special Issue seeks to foster a deeper understanding of the mathematical foundations crucial to advancing the capabilities and efficiency of AI technologies.
Prof. Dr. Zhaoxian Zhou
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 100 words) can be sent to the Editorial Office for announcement on this website.
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-blind 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.
Keywords
- machine learning
- deep learning
- neural networks
- image processing
- pattern recognition
- computer vision
- mathematical methods
- optimization algorithms
- statistical models
- autonomous systems
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.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue policies can be found here.
