Multi-Task Deep Learning for Image Fusion and Segmentation
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 13529
Special Issue Editors
Interests: few-shot learning; remote sensing/hyperspectral imaging; natural language processing; AI safety and security; equivariant architectures and applications of harmonic analysis to problems in machine learning
Interests: geographic information systems (GIS); remote sensing; spatial modeling; and data mining for urban and environmental analysis and planning; mapping urban land cover (green space, impervious surfaces, etc.); monitoring forest health using fine resolution satellite imagery
Special Issues, Collections and Topics in MDPI journals
Interests: land cover mapping; urban remote sensing; machine learning; deep learning; geoinformation; very high resolution; object-based image analysis; big data; automation; change detection; uncertainty; human geography
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Typically, a deep learning model is trained to perform a single task with high accuracy; for example classifying images. Multi-task deep learning is a technique in machine learning where a deep model is trained to perform several tasks (e.g., classify an image, segment out the object, and predict the depth) with different metrics and a collection of shared representations. By training the model across several related tasks, the model develops features which are less prone to overfitting on the training data and thus generalizes better. This technique has shown great success in image and textual analysis. In this special issue, we consider the applicability of this technique to problems arising in remote sensing such as scene segmentation, image fusion, image registration, object detection, super resolution, and anomaly detection.
Dr. Doster Timothy J
Dr. Brian Alan Johnson
Dr. Lei Ma
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
- Multi-task learning
- Image fusion
- Pansharpening
- Segmentation
- Image registration
- Parameter sharing
- Remote sensing
- Convolution neural networks
- Domain adaptation
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue polices can be found here.
