AI-Driven Remote Sensing Image Processing and Pattern Recognition
A special issue of Journal of Imaging (ISSN 2313-433X). This special issue belongs to the section "Computer Vision and Pattern Recognition".
Deadline for manuscript submissions: 31 July 2026 | Viewed by 180
Special Issue Editors
Interests: deep learning; image processing; remote sensing; hyperspectral remote sensing
Interests: hyperspectral remote sensing; remote sensing; multi-modal remote sensing; artificial intelligence; deep learning
Special Issues, Collections and Topics in MDPI journals
Interests: image processing; remote sensing; pattern recognition
Interests: hyperspectral image processing; remote sensing; deep learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The field of remote sensing imaging science is undergoing a transformative era, driven by advancements in artificial intelligence, sensor technology, and computational power. This Special Issue, "AI-Driven Remote Sensing Image Processing and Pattern Recognition," seeks to highlight cutting-edge research and comprehensive reviews that address the evolving landscape of extracting meaningful information from complex remote sensing image data.
This Special Issue aims to focus on novel methodologies that enhance the capabilities of remote sensing image analysis systems. Topics of interest include, but are not limited to, the following: Deep learning architectures (CNNs, transformers, GANs) for remote sensing image segmentation, remote sensing image detection, and remote sensing image classification; explainable AI (XAI) for interpretable model decisions; multi-modal and cross-domain remote sensing data fusion; and robust algorithms for low-quality or adversarial data. A key emphasis will be on practical challenges such as remote sensing data efficiency, model generalization, real-time processing, and integration with emerging imaging modalities.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Advanced deep learning architectures for remote sensing (e.g., transformers, generative models);
- Multimodal and multi-temporal remote sensing data fusion;
- Explainable AI for remote sensing image analysis;
- Scalable and efficient processing techniques;
- Robustness to noise, occlusion, and atmospheric conditions;
- Real-time processing and automated systems.
We look forward to receiving your contributions.
Dr. Zhenqi Liu
Dr. Jiaxin Li
Dr. Mengying Xie
Dr. Chuan Fu
Dr. Kaiwen Wei
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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Imaging is an international peer-reviewed open access monthly 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 1800 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
- remote sensing
- image segmentation
- deep learning
- object detection
- pattern recognition
- computer vision
- multimodal data fusion
- explainable AI (XAI)
- image classification
- computational imaging
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