Intelligent Computing and Remote Sensing—2nd Edition
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 April 2025 | Viewed by 6109
Special Issue Editors
Interests: space perception and intelligent computing; data fusion
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing image processing; visual computing; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing image understanding; hyperspectral image processing; artificial intelligence oceanography
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The previous Special Issue showcased the fusion of intelligent computing and remote sensing, addressing key challenges in the field. Building on its success, we are excited to announce the 2nd Edition.
This upcoming Special Issue aims to continue exploring the applications of intelligent computing in remote sensing, welcoming submissions on image processing, on-board information processing, big data analysis, and UAV systems. We invite theoretical research, practical applications, reviews, and surveys.
This is a platform for cutting-edge research and advancements in intelligent computing and remote sensing. Join scholars and experts globally to drive innovation in this field. Contribute to this Special Issue, shaping the future of intelligent computing in remote sensing.
Dr. Qizhi Xu
Dr. Jin Zheng
Dr. Feng Gao
Guest Editors
Manuscript Submission Information
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Keywords
- deep learning
- on-orbit/on-board real-time computing
- advanced image processing
- remote sensing big data
- UAV information intelligent computing
- radar information intelligent computing
- information fusion
- video imaging satellite intelligent computing
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Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Insulator defect detection model for low-quality images captured by drones
Author: Zou
Highlights: 1. Generation of high-quality images using a patch diffusion model.
2. A Spatial Information Interaction Modul (SIIM) is used to enhance information interaction, improving identification ac-curacy with precise spatial details.
3. The Feature Convergence Module (FCM) serves as a bridge between the dual encoders, integrating the global information from the Swin Transformer into CNN features to enhance identification accuracy.