Self-Supervised Learning for Image Processing and Analysis

Dear Colleagues,

In the rapidly evolving field of deep learning, self-supervised learning has emerged as a groundbreaking approach that leverages unlabeled data to learn meaningful representations. This Special Issue aims to showcase the latest advancements in self-supervised deep learning techniques and their applications in image processing and analysis. We invite researchers and practitioners to submit original research and review articles that contribute to the theoretical foundations, algorithmic advancements, and diverse applications of self-supervised deep learning in image processing and analysis.

Topics of Interest

We welcome submissions on a wide range of topics related to self-supervised deep learning for image processing and analysis, including, but not limited to, the following:

• Novel self-supervised learning models and algorithms for image processing.
• Advances in contrastive learning, clustering, and generative models in the context of image analysis.
• Applications of self-supervised learning in medical imaging, remote sensing, and multimedia analysis.
• Self-supervised learning for image segmentation, classification, and enhancement.
• The integration of self-supervised learning with other unsupervised, semi-supervised, and supervised learning paradigms.
• Evaluation metrics and benchmarks for self-supervised learning in image processing.
• The interpretability and explainability of self-supervised deep learning models for image analysis.
• Challenges and opportunities in deploying self-supervised learning models in real-world scenarios.

Dr. Chuang Niu
Dr. Qian Wang
Dr. Xin Cao
Dr. Shenghan Ren
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. 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.

• self-supervised learning
• unsupervised learning
• image processing
• image analysis
• semi-supervised learning
• weakly supervised learning
• medical imaging
• medical image analysis
• remote sensing imagery