AI-Driven Remote Sensing and 3D Vision Technologies: Methods and Applications
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electronic Multimedia".
Deadline for manuscript submissions: 15 December 2026 | Viewed by 108
Editors
Interests: crack detection; image recognition; multi-scale CNN extraction; high-resolution UAV images; machine learning; deep learning; data mining; performance evaluation of construction; construction risk management
Special Issues, Collections and Topics in MDPI journals
Interests: fuzzy logic; linguistic algorithms; natural language processing; military domain knowledge discovering; soft computing; risk assessment; supply chain; reliability
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advances in artificial intelligence, remote sensing, and 3D vision technologies have significantly transformed the acquisition, processing, interpretation, and application of spatial, visual, and structural information. UAV imagery, satellite data, LiDAR point clouds, photogrammetric models, depth sensing, and 3D reconstruction techniques now provide rich data sources for intelligent perception and decision-making. At the same time, machine learning, deep learning, multi-scale convolutional neural networks, and vision foundation models have enabled more accurate image recognition, object detection, and semantic segmentation across diverse application domains.
This Special Issue, “AI-Driven Remote Sensing and 3D Vision Technologies: Methods and Applications,” aims to provide a platform for presenting innovative theories, algorithms, systems, and practical applications related to AI-enhanced remote sensing and 3D visual analysis. The focus of this collection includes, but is not limited to, remote sensing image processing, UAV-based visual inspection, 3D vision, 3D sensing, and reconstruction technologies.
This Special Issue welcomes original research articles and review papers that explore advanced AI-based methods for extracting, fusing, analyzing, and interpreting remote sensing and 3D vision data. Particular attention will be given to studies that address multi-scale feature extraction, multimodal data fusion, model robustness, explainability, computational efficiency, and real-world implementation.
The existing literature has made substantial progress in remote sensing image analysis, computer vision, and 3D sensing. However, there remains a need for more integrated studies that connect AI-driven sensing technologies with real-world scientific, engineering, and societal applications. This Special Issue seeks to supplement the existing literature by highlighting interdisciplinary approaches that bridge algorithm development, sensing technology, and domain-specific applications.
We look forward to receiving your contributions.
Dr. Ching-Lung Fan
Prof. Dr. Kuei-Hu Chang
Guest Editors
Manuscript Submission Information
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Keywords
- AI-driven methods
- remote sensing
- 3D vision
- deep learning
- machine learning
- object detection
- semantic segmentation
- image recognition
- multi-scale feature extraction
- vision-language model
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