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Optical Aerial Image Segmentation

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 July 2021) | Viewed by 526

Special Issue Editors


E-Mail Website
Guest Editor
Department of Supercomputers and General Informatics, Samara National Research University, 443086 Samara, Russia
Interests: computational imaging; deep learning; hyperspectral imaging; remote sensing

E-Mail Website
Guest Editor
Department of Electrical and Microelectronic Engineering, Rochester Institute of Technology, Rochester, NY 14623, USA
Interests: image classification; artificial intelligence; machine learning; computer vision; robotics

Special Issue Information

Dear Colleagues,

I am delighted to invite you to submit manuscripts for a Special Issue of the journal of Remote Sensing on “Optical Aerial Image Segmentation”. In recent times, the rapid development of remote sensing techniques has significantly increased the quantity and quality of remote sensing images available to characterize various objects on the Earth’s surface, such as buildings and streets, airplanes and vessels, etc. This continues to push research in the area of airborne image segmentation and related topics and plays a basic role in remote sensing image interpretation and different applications. This Special Issue will cover new developments and recent advances in the design of conventional and deep-learning-based methods for segmentation, releases of new datasets, interpretation, applications, and performance evaluation of aerial image segmentation based on different remote sensing platforms. Original research work, letters, and review papers based on theoretical, numerical, and experimental data are welcomed in this Special Issue. The topic includes but is not limited to the following:

  • Optical image segmentation in remote sensing;
  • Hyperspectral image segmentation and image fusion;
  • Learning for aerial image segmentation;
  • New datasets and platforms for aerial image segmentation;
  • Applications of optical aerial image segmentation, e.g., to map creation and analysis, precision agriculture, smart cities, etc.

We look forward to receiving your proposals.

Prof. Dr. Artem V. Nikonorov
Dr. Sildomar T. Monteiro
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

  • remote sensing
  • aerial optical imaging
  • image segmentation
  • deep learning for remote sensing
  • aerial imaging datasets
  • semantic segmentation

Published Papers

There is no accepted submissions to this special issue at this moment.
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