Deep Neural Networks for Remote Sensing Scene Classification
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "AI Remote Sensing".
Deadline for manuscript submissions: closed (1 December 2022) | Viewed by 12367
Special Issue Editors
Interests: remote sensing; hyperspectral image processing; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; machine learning; deep learning; image processing
Interests: pattern recognition; computer vision and spectral imaging with their applications to remote sensing and environmental informatics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the rapid growth of remote sensing data, processing and understanding remote sensing scene images has become more and more important. Owing to their powerful learning ability, deep learning techniques have been widely used in remote sensing data processing and analysis, which will be a feasible solution for remote sensing scene classification and interpretation. Currently, new deep network architectures need to be paid more attention as more suitable tools to develop for remote sensing scene classification, segmentation, detection and higher-level understanding. Therefore, boosting the development of deep networks in remote sensing scene classification is urgent and of vital importance in the field of remote sensing.
This Special Issue aims to develop state-of-the-art deep networks for more accurate remote sensing scene classification and recognition.
This Special Issue will accept topics regarding remote sensing scene classification, segmentation, detection, and understanding-related works. These include, but are not limited to, the following topics:
- Deep networks for remote sensing image scene classification;
- Deep networks for remote sensing image scene segmentation;
- Deep networks for remote sensing image scene detection;
- Remote sensing image scene benchmark datasets;
- Remote sensing image feature extraction and selection;
- Remote sensing image enhancement and fusion.
Dr. Danfeng Hong
Dr. Jing Yao
Dr. Jun Zhou
Guest Editors
Manuscript Submission Information
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Keywords
- deep learning
- remote sensing
- feature extraction
- classification and recognition
- artificial intelligence
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