Mathematical Foundations and Advanced Applications of Machine Learning in Image Processing 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: 30 June 2026 | Viewed by 6
Special Issue Editors
Interests: computer vision; interactive media; machine learning
Special Issue Information
Dear Colleagues,
Machine learning has become a central tool in image processing and computer vision, enabling groundbreaking advances in fields ranging from autonomous vehicles to healthcare, robotics, and multimedia. However, bridging the gap between cutting-edge algorithmic developments and their practical, domain-specific implementations remains a critical challenge.
The purpose of this Special Issue is to provide a platform for the latest research on advanced applications of machine learning in visual computing. We aim to highlight both theoretical innovations and real-world use cases where machine learning has enhanced visual understanding, interpretation, and synthesis. Topics of interest include, but are not limited to, the following:
- Image classification, segmentation, and object detection;
- Scene understanding and semantic segmentation;
- Image enhancement and restoration;
- Three-dimensional reconstruction and depth estimation;
- Visual tracking and video analysis;
- Generative models (GANs, diffusion models) for image synthesis;
- Medical image analysis and diagnostic tools;
- Edge AI and deployment in resource-constrained environments;
- Explainability and interpretability in vision models;
- Multimodal approaches integrating visual and textual or sensor data.
We welcome submissions of original research articles, reviews, and short communications that reflect novel approaches, performance evaluations, or interdisciplinary applications involving machine learning in image processing and computer vision.
Dr. Ju Shen
Dr. Tam Nguyen
Guest Editors
Manuscript Submission Information
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Keywords
- image classification, segmentation, and object detection
- scene understanding and semantic segmentation
- image enhancement and restoration
- 3D reconstruction and depth estimation
- visual tracking and video analysis
- generative models (GANs, diffusion models) for image synthesis
- medical image analysis and diagnostic tools
- edge AI and deployment in resource-constrained environments
- explainability and interpretability in vision models
- multimodal approaches integrating visual and textual or sensor data
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