Mathematics Applications of Artificial Intelligence 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: 10 August 2025 | Viewed by 181
Special Issue Editor
Special Issue Information
Dear Colleagues,
The intersection of Artificial Intelligence (AI), Computer Vision (CV), and mathematical principles serves as a cornerstone for advancing both theoretical understanding and practical applications. This Special Issue, "Mathematics Applications of Artificial Intelligence and Computer Vision", invites researchers to delve into the critical role mathematics plays in shaping AI and CV methodologies. By emphasizing mathematical rigor, this Special Issue aims to explore innovative approaches in feature extraction, geometric modeling for image analysis, optimization techniques, and the development of interpretable and robust deep learning algorithms.
The focus extends to the application of mathematical methods in addressing real-world challenges, improving system efficiency, and enhancing understanding. Topics of interest include, but are not limited to, theoretical advancements in image analysis, mathematical formulations for pattern recognition, novel deep learning schemes, and breakthroughs in computational intelligence, with applications in vision-related tasks. Contributions may comprise original research or reviews that integrate mathematics with the evolving fields of AI and CV.
This Special Issue seeks to bridge mathematical theory with its transformative applications in computer vision and artificial intelligence by encouraging a multidisciplinary perspective and fostering innovation in both academic research and industry practice.
I look forward to receiving your contributions.
Dr. Dimitrios Tsourounis
Guest Editor
Manuscript Submission Information
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Keywords
- computer vision
- artificial intelligence
- mathematical modeling
- image processing
- deep learning
- pattern recognition
- geometric methods
- knowledge distillation
- optimization techniques
- computational intelligence
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