Deep Learning-Based Small-Target Detection in Remote Sensing—2nd Edition

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. Recent advances in artificial intelligence have opened new opportunities for improving small target detection in remote sensing. At the same time, the increasing availability of multi-source Earth observation calls for innovative methods that effectively integrate diverse sensor characteristics and exploit complementary information.

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 multimodal 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:

• Small target detection in high-resolution optical, SAR, hyperspectral, and thermal remote sensing imagery
• Deep learning architectures and vision foundation models for small object detection in remote sensing
• Noise reduction and contrast enhancement methods for improving target visibility
• Multimodal and multi-sensor fusion strategies for detecting small objects in complex environments
• Change detection, anomaly detection, and open-world recognition for small target discovery
• Advances in SAR 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
Dr. Fei Teng
Prof. Dr. Zhenming Peng
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 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-anonymized 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.