The Future of Image Processing: Leveraging Pattern Recognition and AI
A special issue of AI (ISSN 2673-2688). This special issue belongs to the section "Medical & Healthcare AI".
Deadline for manuscript submissions: 16 May 2026 | Viewed by 1093
Special Issue Editor
Special Issue Information
Dear Colleagues,
Recent advances in artificial intelligence (AI) and pattern recognition have significantly reshaped the landscape of image processing, enabling more robust, efficient, and interpretable methods. The convergence of traditional model-driven approaches with modern data-driven paradigms has led to breakthroughs in image segmentation, recognition, enhancement, and multimodal analysis. As the field continues to evolve, the integration of AI-driven techniques is not only pushing the boundaries of algorithmic innovation but also fostering cross-disciplinary applications with profound societal impact.
This Special Issue aims to bring together state-of-the-art research and comprehensive reviews on how AI and pattern recognition can address emerging challenges in image processing. The scope of this issue encompasses both theoretical and applied perspectives, bridging the gap between fundamental methodologies and real-world deployment. Specifically, it seeks to provide a platform for novel theories, algorithms, frameworks, and applications that enhance the interpretability, scalability, and reliability of image processing.
In relation to the existing literature, this Special Issue intends to serve as a complementary collection that goes beyond isolated advances by emphasizing the synergy between classical model-driven techniques and data-driven deep learning paradigms. While the current body of research lies in either algorithmic novelty or domain-specific applications, few collections provide a holistic view that integrates methodological innovation with interdisciplinary practices across diverse domains such as medical imaging, remote sensing, cultural heritage preservation, and industrial inspection. By highlighting both fundamental and application-oriented research, this Special Issue will provide readers with a coherent reference point and guide future directions for the community.
In this Special Issue, both original research articles and comprehensive review papers are welcome. Research areas may include, but are not limited to, the following:
- Image enhancement and restoration techniques.
- Multimodal and cross-domain data fusion.
- Deep learning-based vision models and architectures.
- Unsupervised, self-supervised, and zero-shot image segmentation.
- Interpretable and trustworthy AI for imaging.
- Domain adaptation and transfer learning in vision.
- AI applications in medical diagnosis, remote sensing, cultural heritage, and industrial quality inspection.
We look forward to receiving your contributions.
Prof. Dr. Hongjian Shi
Guest Editor
Manuscript Submission Information
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Keywords
- image processing
- pattern recognition
- image segmentation
- image classification
- medical imaging
- interpretable AI
- multimodal analysis
- domain adaptation
- medical imaging
- remote sensing
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