Computational Intelligence for Remote Sensing Image Analysis and Applications
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: closed (20 October 2023) | Viewed by 16329
Special Issue Editors
Interests: computational intelligence; remote sensing images understanding; change detection; deep learning
Special Issues, Collections and Topics in MDPI journals
Interests: computational intelligence; evolutionary computation; neural networks; multi-objective optimization
Special Issues, Collections and Topics in MDPI journals
Interests: machine learning; evolutionary computation; computer vision; services computing; pervasive computing
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; deep learning; artificial intelligence; image processing; signal processing
Special Issues, Collections and Topics in MDPI journals
Interests: hyperspectral remote sensing; neural networks; computational intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Nowadays, remote sensing systems and technology have been intensively studied and widely applied for earth observation, environmental monitoring, land survey, disaster management, etc. The massive amount of remote sensing imagery data generated from various types of sensors mounted in satellites, aircrafts, and UAVs pose great challenges to data storage, management, and analysis. Meanwhile, security and privacy from the aspects of both data and techniques attract greater attention. In various applications based on remote sensing imagery data, there exist many optimization tasks which may not be well dealt with via conventional mathematical programming approaches due to a non-convex and/or a non-differentiable problem nature, or due to a lack of explicit mathematical formulations.
Computational intelligence (CI) is one of the most prosperous AI sub-fields, studying on computational methodologies and approaches inspired by the intelligent behaviors that occur in nature and biology to resolve complex problems, in which traditional approaches demonstrate ineffectiveness or infeasibility. It involves neural networks, evolutionary computation, and fuzzy logic as three major research areas, which has been successfully applied in remote sensing. Particularly, deep neural networks have achieved great successes in tons of remote sensing image analysis tasks, ranging from segmentation and classification to detection and super-resolution.
Topics To Be Covered
This Special Issue intends to provide a forum for disseminating the achievements related to the research and applications of CI-relevant techniques for analyzing remote sensing images of various modalities, e.g., multi/hyperspectral, SAR, and LIDAR images. The topics of this Special Issue include, but are not limited to:
- CI for remote sensing image denoising, restoration or super-resolution;
- CI for remote sensing image registration;
- CI for remote sensing image segmentation, classification, and retrieval;
- CI for image-based target detection and recognition in remote sensing;
- CI-based feature selection, extraction and learning techniques for remote sensing image analysis;
- CI for remote sensing image data fusion or compression;
- CI for multi-temporal remote sensing image analysis, e.g., change detection;
- Transfer learning and federated learning in CI-based remote sensing image analysis;
- Security and privacy in CI-based remote sensing image analysis;
- CI for large-scale or real-time remote sensing image analysis;
- Applications: earth observation, land survey, mining, disaster management, navigation, etc.
Dr. Jiao Shi
Prof. Dr. Maoguo Gong
Prof. Dr. Kai Qin
Dr. Gwanggil Jeon
Dr. Yu Lei
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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Keywords
- remote sensing
- deep learning
- computational intelligence
- multi-task learning
- image processing
- hyperspectral and multispectral imaging
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