Artificial Intelligence-Based Sensor Data Processing for Remote Sensing
A special issue of Sensors (ISSN 1424-8220).
Deadline for manuscript submissions: 15 August 2025 | Viewed by 197
Special Issue Editors
Interests: artificial intelligence; radar signal processing
Special Issues, Collections and Topics in MDPI journals
Interests: machine learning using radar signals; distributed radar system
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue deals with the various artificial intelligence algorithms that can be used in remote sensing. In particular, it will cover signal and image processing techniques and sensor fusion systems for sensors widely used in remote sensing, such as cameras, lidar, and radar. It will also introduce artificial intelligence and deep learning-based methods for this purpose.
Including sensing in indoor and outdoor environments, this Special Issue will introduce research related to remote sensing in environments such as ground and space. It also aims to cover various artificial intelligence-based algorithms related to target detection, tracking, recognition, and identification techniques. Artificial intelligence algorithms can be applied in many areas of remote sensing, and studies on various datasets and experimental results will also be comprehensively covered.
Our suggested themes and article types for submissions including but not limited to:
- Artificial intelligence/deep learning for remote sensing;
- Sensors (e.g., camera, lidar, and radar) for remote sensing;
- Fusion of heterogeneous sensor data;
- Datasets for AI and deep learning;
- AI-based signal/image processing for remote sensing.
You may choose our Joint Special Issue in Remote Sensing.
Prof. Dr. Seongwook Lee
Dr. Byung-Kwan Kim
Guest Editors
Manuscript Submission Information
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Keywords
- remote sensing
- artificial intelligence/deep learning
- sensors (e.g., camera, lidar, radar)
- sensor fusion
- signal/image processing
- target detection and tracking
- target recognition and classification
- image segmentation
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