Remote Sensing and Machine Learning of Signal and Image Processing
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "AI Remote Sensing".
Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 38623
Special Issue Editors
Interests: remote sensing image processing; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: knowledge graph; deep learning; big data mining
Special Issues, Collections and Topics in MDPI journals
2. Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Münchener Straße 20, 82234 Weßling, Germany
Interests: remote sensing; computer vision; machine/deep learning
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing image processing; hyperspectral remote sensing; deep learning in remote sensing; change detection in remote sensing; remote sensing applications in urban planning; geospatial data analysis and modeling; SAR remote sensing
Special Issues, Collections and Topics in MDPI journals
Interests: machine learning; computation intelligence; evolutionary computation; image processing; pattern recognition
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the development of remote sensing (RS) observation technology, many remote sensing images can be produced daily. These remote sensing images contain rich information to support various applications, such as urban planning, land resource management, etc. Exploring the important knowledge from those abundant RS images effectively is a necessary and urgent task. Diverse machine learning methods have recently been used to interpret RS images, accelerating intelligent interpretation in the remote sensing community. However, due to the complex contents of RS images and specific application requirements, progressive technologies still need to be explored to fully understand RS images. This Special Issue encourages the submission of papers on advanced machine learning and image processing techniques for remote sensing. We welcome topics that include but are not limited to:
- Remote sensing land-cover/scene classification;
- Content-based remote sensing image retrieval;
- Remote sensing object detection;
- Remote sensing change detection;
- Multimodel fusion for remote sensing;
- Remote sensing super-resolution.
Dr. Xu Tang
Dr. Yansheng Li
Prof. Dr. Lichao Mou
Prof. Dr. Xiangrong Zhang
Prof. Dr. Licheng Jiao
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
- machine learning
- remote sensing
- signal processing
- change detection
- scene classification
- object detection
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