Applications of Machine Learning Algorithms in Remote Sensing

Dear Colleagues,

Deep learning-based techniques have been introduced in a wide range of applications, like the analysis of remote sensing images, owing to the rising accessibility of large-scale data sets, efficient training approaches, and high-performance computing devices. In the past few years, models based on deep learning have become a potent tool for analyzing imagery from satellites for a range of tasks, including classification, clustering, forecasting, and regression. Applying machine learning methods invented for computer vision to remote sensing data that is substantial, multivariate, noisy, and irregularly collected presents unseen challenges. Review and research papers on cutting-edge CNN and vision transformer-based methods for deep learning, architectures, and structures for applications in remote sensing will be published in this Special Issue, with an emphasis on tasks that address the problems in the field.

Potential topics of interest include, but are not limited to:

• Shallow and deep learning remote sensing image interpretation and analysis (image classification, pan-sharpening, image enhancement, object detection, semantic segmentation, and change detection)’
• Graph, adversarial, unsupervised, semi-supervised, self-supervised, active, and transfer learning for dealing with limited and/or low-quality data;
• Knowledge acquisition of deep learning models for remote sensing imagery;
• Novel benchmark datasets for remote sensing image analysis;
• Applications of vision transformers (ViTs) in remote sensing.

Dr. Ali Jamali
Dr. Bing Lu
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. Applied Sciences 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 2400 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.

• machine learning
• deep learning
• CNNs
• vision transformer
• geography