Special Issue "Artificial Intelligence-Based Learning Approaches for Remote Sensing"
Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 9833
Interests: image processing; particularly image compression; motion estimation; demosaicking;and image enhancement; computational intelligence; fuzzy and rough sets theories
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Special Issue in Remote Sensing: Computational Intelligence for Remote Sensing Image Analysis and Applications
Special Issue in Remote Sensing: Advanced Machine Learning and Deep Learning Approaches for Remote Sensing
Remote sensing is a tool for comprehending the earth and supporting human–earth communications. Recent advances in remote sensing have led to a high-resolution monitoring of Earth on a global scale, providing a massive amount of earth observation data. These data must be processed with new levels of accuracy, complexity, security, achievement, and reliability. Therefore, applicable and consistent research on artificial intelligence-based learning methods and its applied image processing are needed for remote sensing. These methods can be general and specific tools of artificial intelligence, including regression models, neural networks, decision trees, information retrieval, reinforcement learning, graphical models, and decision processes. We trust that artificial intelligence, deep learning and data science methods will provide promising tools to overcome many challenging issues in remote sensing in terms of accuracy and reliability. This Special Issue is the second edition of “Advanced Machine Learning for Time Series Remote Sensing Data Analysis”. In this second edition, our new Special Issue aims to report the latest advances and trends concerning the advanced artificial learning and data science techniques to the remote sensing data processing issues. Papers of both theoretical and applicative nature, as well as contributions regarding new advanced artificial learning and data science techniques for the remote sensing research community, are welcome.
Dr. Gwanggil Jeon
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 2500 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.
- AI (architectures, models, learning, etc.) and data science approach for remote sensing
- Explainable and interpretable machine learning
- HPC-based and distributed machine learning for large-scale image analysis
- Reinforcement learning for remote sensing
- Information retrieval for remote sensing
- Big data analytics for beyond 5G
- Edge/fog computing for remote sensing
- IoT data analytics in remote sensing
- Data-driven applications in remote sensing