Mathematical Methods and Machine Learning Algorithms for Pattern Recognition and Image Analysis
A Special Issue of Mathematics (ISSN 2227-7390) belonging to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: 20 May 2027 | Viewed by 9
Editor
Interests: computer vision; information retrieval; deep learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The growing reliance on mathematically principled solutions has become essential to overcoming the brittleness of purely empirical machine learning models in pattern recognition and image analysis. While deep learning remains dominant, persistent challenges such as adversarial attacks, domain shifts, label scarcity, and lack of interpretability call for fresh advances in optimization, geometry, and probability theory. Contemporary research actively explores non‑convex analysis, manifold learning, tensor decompositions, and topological data analysis to deliver algorithms with provable convergence, robustness, and transparency. Meanwhile, the surge in multi‑modal, high‑resolution imagery, combined with the pressing need for real‑time and resource‑efficient deployment, creates an ideal testing ground for mathematical solvers that bridge theory and application, making this topic highly relevant for both academia and industry. Aim and scope: This Special Issue seeks to collect and disseminate cutting‑edge machine learning algorithms grounded in novel mathematical frameworks for pattern recognition and image analysis. We welcome contributions that introduce rigorous solvers, spanning representation learning, image analysis, lightweight neural architectures, and cross‑modal pattern recognition, with a focus on theoretical guarantees, computational efficiency, and practical resilience.
Topics of interest for publication include, but are not limited to, the following:
- self-supervised and semi-supervised representation learning;
- explainability and fairness algorithms;
- federated learning and privacy-preserving image analysis;
- lightweight neural networks and edge inference;
- cross-modal and spatiotemporal sequence pattern recognition.
Dr. Gengshen Wu
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
- machine learning
- pattern recognition
- image analysis
- mathematical optimization
- robustness and interpretability
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