Remote Sensing Image Thorough Analysis by Advanced Machine Learning
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: 28 February 2025 | Viewed by 158
Special Issue Editors
Interests: remote sensing; image processing; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; image processing; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: image processing; machine learning; pattern recognition
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Remote sensing imaging captures electromagnetic radiation in various wavelengths, such as visible and infrared, reflected or emitted from Earth's surface or atmosphere using sensors mounted on aircrafts and satellites, which provides valuable information about the physical properties and characteristics of the observed area in a non-invasive and cost-effective manner. Thus, remote sensing images can be widely utilized in fields like environmental monitoring, agriculture, disaster response, urban planning, and geological exploration. The merits of such wide applications include thorough analyzing the semantic content of each image using advanced machine learning techniques.
Although machine learning techniques, especially the deep learning, have inspired great success in the domain of remote sensing image analysis, thoroughly analyzing the semantic content of each remote sensing image is still confounded by significant challenges, e.g., difficulty in matching or fusing cross-modality images, limited generalization capacity in cross-domain few-shot or zero-shot settings, expensive computational and memory costs, etc. Therefore, more effort should be paid to exploiting advanced machine learning techniques, e.g., meta-learning, self-supervised learning, large-foundation modeling, to mitigate these challenges and facilitate the wide application of remote sensing images.
For this Special Issue, we encourage submissions that focus on addressing the challenges in thorough remote sensing analysis using advanced machine learning techniques. This Special Issue welcomes high-quality submissions that provide the community with the most recent advancements on all aspects of remote sensing technologies and applications, including but not limited to the following:
- Noisy, rainy, and foggy remote sensing image restoration;
- Spatial and spectral remote sensing image super-resolution;
- Remote sensing image matching;
- Multi-modal remote sensing image fusion;
- Remote sensing image segmentation;
- Remote sensing object detection;
- Remote sensing image analysis model acceleration or compression;
- Other topics on applications of remote sensing image analysis.
Prof. Dr. Lei Zhang
Dr. Chen Ding
Prof. Dr. Wei Wei
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.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- image restoration
- image super-resolution
- image matching
- image fusion
- image segmentation
- object detection
- model acceleration or compression
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