Emerging Remote Sensing Techniques and Applications for Object Detection

Dear Colleagues,

Object detection is a fundamental but challenging problem in the field of remote sensing. With different types of data sources, such as UAVs, airplanes, satellites, spacecraft, etc., it has a wide range of applications, such as environmental monitoring, dynamic object monitoring, geological hazard detection, land-use/land-cover mapping, change detection, geographic information system update, precision agriculture, urban planning, landing site selection and estimation, exploration planning, etc.

The latest research on this area has been making great progress in many directions. With the continuous improvement of the hardware conditions and the gradual innovation of image processing technology, new techniques, methods and applications for object detection have emerged in the field of remote sensing in recent years.

This Special Issue aims to bring together researchers from academia, industry, and government agencies to understand the innovative technologies in the field of object detection in remote sensing. Submitted papers are expected to employ state-of-the-art and novel approaches to cover solutions for object detection related, but not limited, to the following topics:

• Innovative theories and approaches for object detection and its applications using remote sensing data such as optical images, laser, SAR data, etc.;
• Object detection methods and applications using remote sensing data captured using UAVs, airplanes, satellites, spacecraft, etc.;
• Fusion of multi-sensor data for object detection;
• Deep learning for object detection, image classification, and semantic and instance segmentation;
• Supervised, weakly supervised, and unsupervised machine learning for object detection using remote sensing data;
• Imbalance problem (classes, scales, spatial, and objectives) solutions;
• Object detection in challenging conditions;
• Transfer learning, and deep reinforcement learning for object detection using remote sensing data.

Dr. Yexin Wang
Dr. Yi Cui
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. Sensors 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 2600 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.

• remote sensing
• object detection
• emerging techniques
• deep learning
• segmentation
• satellite image