Recent Progress and Challenges in Computer Vision and Machine Learning
A special issue of Journal of Imaging (ISSN 2313-433X). This special issue belongs to the section "Computer Vision and Pattern Recognition".
Deadline for manuscript submissions: 30 November 2026 | Viewed by 196
Special Issue Editor
Special Issue Information
Dear Colleagues,
Recent years have witnessed rapid advances in computer vision and machine learning, driven by the emergence of large-scale data, powerful representation learning models, and increasingly integrated multimodal systems. From foundational vision tasks such as recognition, detection, and reconstruction to higher-level reasoning, generation, and decision-making, modern visual intelligence systems are becoming more general, controllable, and applicable to complex real-world scenarios. At the same time, these advances also bring forward new challenges related to robustness, generalization, interpretability, data efficiency, and deployment in domain-specific settings.
This Special Issue aims to provide a comprehensive forum for presenting recent progress, open challenges, and future directions in computer vision and machine learning. We welcome contributions that span theoretical developments, algorithmic innovations, and practical systems, with particular emphasis on the interaction between vision models and modern learning paradigms such as deep learning, generative modeling, and multimodal large language models. Topics of interest include, but are not limited to, controllable and interpretable visual generation, vision–language understanding, multimodal representation learning, robust and trustworthy vision systems, and applications in domains such as medicine, architecture, remote sensing, and the Internet.
By bringing together researchers from both academia and industry, this Special Issue seeks to highlight emerging trends, identify key challenges, and stimulate cross-disciplinary discussions that advance the state of the art in computer vision and machine learning.
Dr. Qi Chen
Guest Editor
Manuscript Submission Information
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Keywords
- computer vision
- machine learning
- multimodal learning
- vision–language models
- generative models
- controllable and interpretable AI
- large language models
- robust visual understanding
- real-world applications
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