Computer Vision and Pattern Recognition Based on Remote Sensing
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".
Deadline for manuscript submissions: 31 March 2025 | Viewed by 119
Special Issue Editors
2. Machine Vision Technology Innovation Center of Hebei Province, Baoding 071002, China
3. National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
Interests: computer vision and multidimensional signal processing
Special Issues, Collections and Topics in MDPI journals
Interests: image processing; signal processing
Interests: explainable deep learning; medical image analysis; pattern recognition and medical sensors; artificial intelligence; intelligent computing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue entitled “Computer Vision and Pattern Recognition Based on Remote Sensing” focuses on the latest advancements in and research on utilizing computer vision and pattern recognition techniques to analyze and interpret remote sensing data. Remote sensing technology, which captures information about the Earth's surface from a distance, has become increasingly important in various fields such as urban planning, environmental monitoring, agricultural management, disaster assessment, and map updating. The integration of computer vision and pattern recognition methods with remote sensing data has significantly enhanced our ability to detect, analyze, and understand changes in the environment at large scales and with high accuracy.
This Special Issue showcases cutting-edge research on the development of novel algorithms, frameworks, and applications that leverage remote sensing data for visual analysis, object recognition, scene comprehension, and change detection. The contributions will cover a wide range of topics, including but not limited to:
- Image processing for remote sensing;
- Object recognition and instance segmentation;
- Defect detection in industrial surfaces;
- Cross-domain object detection;
- Multimodal detection for autonomous driving;
- Advanced network architectures for remote sensing image analysis.
Prof. Dr. Shuaiqi Liu
Dr. Qi Hu
Prof. Dr. Yudong Zhang
Guest Editors
Manuscript Submission Information
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Keywords
- image processing
- object recognition
- remote sensing
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