Deep Learning-Based Small-Target Detection in Remote Sensing
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: 15 September 2025 | Viewed by 227
Special Issue Editors
Interests: image processing; infrared target detection; remote sensing image processing
Special Issues, Collections and Topics in MDPI journals
Interests: infrared small-target detection; remote sensing image processing; deep learning
Special Issues, Collections and Topics in MDPI journals
Interests: synthetic aperture radar image processing; synthetic aperture radar target detection and feature analysis
Interests: small-target detection; reinforce-learning; machine learning; remote sensing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Small target detection in remote sensing is a challenging task due to the limited pixel representation of targets, complex backgrounds, and varying environmental conditions. Recently, the application of deep learning techniques has demonstrated significant improvements in detecting small objects in remote sensing imagery.
This Special Issue aims to explore cutting-edge developments in deep learning-based small target detection, with a strong focus on remote sensing data acquisition, preprocessing, and multi-sensor integration. We encourage contributions that investigate sensor-driven enhancements, geospatial data fusion, and innovative applications of AI to detect small targets under complex observation conditions. Topics of interest include, but are not limited to, the following:
- Small target detection in high-resolution optical, Synthetic Aperture Radar, hyperspectral, and thermal remote sensing imagery
- Deep learning models tailored for small target identification in remote sensing data
- Noise reduction and contrast enhancement methods for improving target visibility
- Multi-sensor fusion strategies for detecting small objects in complex environments
- Change detection and anomaly-based approaches for identifying small targets
- Advances in Synthetic Aperture Radar imaging techniques combined with AI for small object recognition
- Spatio-temporal modeling of small target movement using remote sensing and AI
- UAV-based remote sensing for real-time small target detection and tracking
- Applications in environmental monitoring, disaster response, maritime surveillance, and security
We look forward to receiving your contributions.
Dr. Yuhan Liu
Prof. Dr. Zhenming Peng
Dr. Fei Teng
Dr. Xiaoyang Wang
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
- small target detection
- deep learning
- remote sensing image processing
- hyperspectral and infrared sensing
- multi-sensor data fusion
- feature extraction
- target recognition
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