Image Analysis Technology Based on Artificial Intelligence
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 November 2026 | Viewed by 60
Special Issue Editors
Interests: computer vision; autonomous driving; embodied AI; multimodal image analysis; generative models; world models; trustworthy
Special Issues, Collections and Topics in MDPI journals
Interests: AI Computational imaging; optical imaging; computer vision; intelligent image processing; hyperspectral imaging; photometric vision; 3D reconstruction; image restoration
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Artificial intelligence is reshaping image analysis by enabling accurate, efficient, and trustworthy interpretation of complex visual data across scientific, industrial, and medical scenarios. Recent advances in deep learning, vision foundation models, generative models, and multimodal learning have substantially improved image restoration, object detection, segmentation, classification, anomaly recognition, and decision support. However, their practical deployment still faces important challenges, including data scarcity, class imbalance, motion blur and other image degradations, cross-domain distribution shifts, limited interpretability, and robustness requirements in real-world environments.
This Special Issue aims to compile high-quality original research and review articles on AI-based image analysis technologies and their applications. Topics of interest include, but are not limited to, deep learning for image detection and segmentation, generative image enhancement and restoration, medical and biological image analysis, industrial inspection, remote sensing, UAV-based visual inspection, multimodal and vision–language image understanding, domain adaptation, self-supervised learning, lightweight and real-time models, uncertainty estimation, verification mechanisms, and trustworthy deployment. We particularly welcome contributions that combine methodological innovation with practical validation in real-world image analysis tasks.
Dr. Xiaosong Jia
Prof. Dr. Yinqiang Zheng
Guest Editors
Manuscript Submission Information
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Keywords
- artificial intelligence
- image analysis
- computer vision
- deep learning
- image segmentation
- object detection
- medical imaging
- industrial inspection
- image restoration
- trustworthy AI
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