Deep Learning Based Target Detection and Recognition in Remote Sensing Images

Dear Colleagues,

Target detection and recognition is a fundamental task in remote sensing, and it plays a significant role in various applications. Tradition algorithms use manually designed features whose representation capability is limited. With the further development of deep learning (DL) techniques, DL-based target detection and recognition approaches have become increasingly popular. Despite substantial progress in the field of DL-based detectors and classifiers with automatically learned features, there are several remaining issues: 1) the performance of tiny targets or target detection in low-resolution images is not satisfactory due to limited information; 2) target detection and recognition with few training samples is still a challenge; techniques such as transfer learning, weakly supervised learning, self-supervised learning and meta learning are possible solutions requiring investigation; 3) current target detection and recognition models are more like black boxes; their interpretability needs to be further studied in order to advance their development in remote sensing images.

This Special Issue aims to provide a platform for researchers to discuss and provide solutions for the above-mentioned issues, contributing to the development of target detection and recognition in remote sensing images.

Topics of interest include, but are not limited to:

• Deep-learning-based target detection, tracking and recognition in visible remote sensing images, infrared remote sensing images or synthetic aperture radar images.
• Advanced remote sensing target detection and recognition techniques for addressing issues including few-shot learning, tiny target detection, fine-grained target recognition, etc.
• Land cover and land use classification, change detection of remote sensing images with one sensor or multiple sensors.
• Investigations on the physical interpretability of target detection and recognition models in remote sensing images.

Dr. Zongxu Pan
Prof. Dr. Fan Zhang
Dr. Xinghua Li
Dr. Bo Tang
Dr. Wei Yao
Dr. Zhongling Huang
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 250 words) can be sent to the Editorial Office for assessment.

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.