Image Fusion and Object Detection Using Multi-modal Remote Sensing Data
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: 31 January 2025 | Viewed by 306
Special Issue Editors
Interests: change detection; deep learning; remote sensing
Special Issues, Collections and Topics in MDPI journals
Interests: thermal infrared remote sensing; deep learning
Special Issue Information
Dear Colleagues,
Multi-modal remote sensing data provide abundant information about ground objects from multiple perspectives. The image fusion technique aims to extract complementary information from source images of different modalities and combine the information to generate images/data with abundant information, which is believed to be conducive to subsequent tasks, such as object detection. Image fusion and object detection have thus attracted extensive attention from the remote sensing community. Despite remarkable successes that have been achieved in recent decades, challenges remain regarding the fast development of multi-modal data collection and artificial intelligence techniques. Considering both data properties and model ability, improving the performance of image fusion and object detection can be possible.
This Special Issue aims to study all techniques designed for image fusion and object detection from multi-modal remote sensing data, ranging from multispectral, hyperspectral, panchromatic, thermal, and SAR data. Topics from conventional machine learning techniques and model-driven techniques to the most recent deep learning techniques may be covered. Applications and reviews about the aforementioned techniques are also welcome for submission to this Special Issue, as they can give helpful guidance for future-related studies. Articles may address, but are not limited, to the following topics:
- Remote sensing image fusion;
- Remote sensing image classification;
- Remote sensing image instance segmentation;
- Object detection and tracking;
- Benchmark dataset creation;
- Deep neural network optimization;
- Multi-modal data analysis and fusion;
- Applications of image fusion;
- Applications of object detection;
- Review of images fusion;
- Review of object detection;
- Review of image classification.
Dr. Bin Yang
Dr. Xin Ye
Dr. Jing Li
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. 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.
Keywords
- image fusion
- object detection
- multi-modal data
- deep learning
- benchmark dataset
- remote sensing data analysis
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