Cutting-Edge Advances in Deep Learning with Symmetry Integration: Exploring the Frontiers of Knowledge
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".
Deadline for manuscript submissions: 31 December 2024 | Viewed by 87
Special Issue Editors
Interests: computer science; data mining; artificial intelligence; human interaction computing; ubiquitous computing
Interests: artificial intelligence (XAI); machine learning; deep learning; medical image processing and analysis; data science; pattern recognition; bioinformatics
Interests: ambient intelligence; signal processing; biomedical engineering; context-aware computing; bioinformatics and game development
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
“Cutting-Edge Advances in Deep Learning with Symmetry Integration: Exploring the Frontiers of Knowledge” is a unique and highly anticipated Special Issue dedicated to showcasing the latest breakthroughs in deep learning, particularly in the context of symmetry. This Special Issue serves as a platform for researchers, scientists, and practitioners to share their pioneering contributions and insights, thereby pushing the boundaries of what is possible in artificial intelligence.
Deep learning has witnessed remarkable growth in recent years, revolutionizing industries ranging from healthcare and finance to autonomous vehicles and natural language processing. As we stand at the forefront of this transformative era, this Special Issue seeks to provide a comprehensive snapshot of the most innovative and game-changing developments in the deep learning landscape, with a particular emphasis on how symmetry concepts are influencing these advancements.
We invite submissions of original research papers, reviews, and cutting-edge case studies that address a broad spectrum of topics within deep learning and its integration with symmetry, including but not limited to the following:
- Deep learning with symmetry integration;
- Symmetry-enhanced artificial intelligence applications;
- Novel architectures and algorithms of deep learning;
- Transfer learning and domain adaptation;
- Explainable AI and interpretability;
- Generative models and creative applications;
- Federated learning and privacy-preserving techniques;
- Scalability and efficiency in deep learning systems;
- Real-world applications in healthcare, robotics, finance, and more.
By participating in this Special Issue, you will contribute to advancing the field of deep learning with a focus on symmetry integration, helping to shape the future of artificial intelligence. We look forward to your submissions and the valuable insights that will emerge from this exceptional collection of research.
Join us in “Cutting-Edge Advances in Deep Learning with Symmetry Integration: Exploring the Frontiers of Knowledge” and be part of the deep learning revolution that is reshaping our world.
Prof. Dr. Juan Pablo García-Vázquez
Dr. Raúl Cruz-Barbosa
Dr. Carlos Eric Galván-Tejada
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. Symmetry 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 2400 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
- deep learning
- neural networks
- generative models
- interpretability
- real-world applications
