Leveraging the Advances in Machine Learning for Object Detection in Earth Observation Data

Dear Colleagues,

Object detection is one of the most important and challenging categories of computer vision and machine learning, which have been extensively utilized in various applications, such as video surveillance, autonomous vehicle, human–machine interaction, medical image analysis, etc.

Developing technology is promoting the development of both highly strong algorithms for the purpose of computer vision tasks, and high spatio-temporal resolution Earth observation data. Researchers are now eager to combine these two branches, and object detection in remote sensing imagery is one of the most important research paths currently. Object detection techniques originate the basis of important applications of marine monitoring, land cover/use mapping, video surveillance, etc. Existing computer vision object detection techniques have been developed for more regular cases such as natural imagery, and remote sensing research has not yet fully explored the advantages of these advances in object detection research. This Special Issue aims to bring ground-breaking research together for the purpose of developing novel remote sensing computational imaging applications in object detection. We also aim to promote new and novel sources of remote sensing imagery from various sensors that have not been explored. Considering the highly complex and advanced conditions that various remote sensing imagery exhibits, the novel research in this Special Issue should aim to promote specially developed novel machine learning architectures for the purpose of object detection. We would like to invite researchers to submit novel pieces of work from all viewpoints, including theory, algorithm development, systems, and environmental and industrial applications.

Dr. Oktay Karakuş
Dr. Igor Rizaev
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.

• object detection
• machine learning
• remote sensing
• computational imaging
• earth observation
• multi-modal
• multi-sensor
• artificial intelligence