Mathematics-Driven Computer Vision and Multi-Modal Learning
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".
Deadline for manuscript submissions: 31 July 2026 | Viewed by 32
Special Issue Editor
Special Issue Information
Dear Colleagues,
This Special Issue of Mathematics focuses on the critical role of mathematics in advancing computer vision and multi-modal learning for remote sensing and low-altitude scene analysis. We seek high-quality articles that explore how mathematical frameworks, such as optimization theory, statistical learning, geometric modeling, signal processing, and differential geometry, drive innovations in these specialized domains. Submissions may cover theoretical advancements, including novel mathematical models for multi-modal data fusion, scene feature representation, or robust inference under complex environmental conditions, as well as practical applications such as enhancing the accuracy of remote sensing image interpretation, low-altitude target detection, or dynamic scene understanding.
We encourage studies that bridge mathematical rigor with real-world challenges in remote sensing and low-altitude scenarios, such as comparing classical and emerging mathematical tools for handling data sparsity, noise, or multi-source heterogeneity or demonstrating how mathematical insights solve critical problems such as multi-modal alignment, small target recognition, or 3D scene reconstruction. Manuscripts that are purely speculative without empirical validation, theoretical proof, or practical application verification will not be considered.
We welcome contributions from researchers worldwide, especially those pioneering cross-disciplinary breakthroughs at the intersection of mathematics, computer vision, multi-modal learning, and the rapidly evolving fields of remote sensing and low-altitude scene analysis.
Dr. Junjie Zhang
Guest Editor
Manuscript Submission Information
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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
- mathematics
- computer vision
- multi-modal learning
- remote sensing
- low-altitude scene analysis
- mathematical modeling
- data fusion
- scene understanding
- optimization theory
- statistical learning
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