Symmetry/Asymmetry in Neural Networks and Applications
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 229
Special Issue Editors
Interests: deep learning; network and information security; anomaly detection
Special Issue Information
Dear Colleagues,
This Special Issue aims to explore the application of symmetry in the field of neural network learning, as well as the application of symmetry and asymmetry to the training of fully supervised, semi-supervised, and unsupervised models. Deep learning models such as the auto-encoder network, adversarial generative network (GAN), graph neural network (GNN), distillation learning, and twin network all exhibit strong symmetry. Applying these techniques in many industrial and agricultural fields, including object recognition, image segmentation, pedestrian re-recognition, image compression, time series prediction, and anomaly detection applications, these deep learning models have shown good performance in many application fields. This Special Issue will look at the future direction of machine learning, especially deep learning theory and practice, inspired by various symmetries.
We are therefore inviting manuscript submissions. Topics of interest include, but are not limited to, the following:
- Target recognition;
- Image segmentation;
- Image compression;
- Medical image processing;
- Action recognition;
- Pedestrian re-recognition;
- Time series prediction;
- Anomaly detection.
Dr. Peishun Liu
Prof. Dr. Ruichun Tang
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
- neural network
- artificial intelligence
- deep learning
- adversarial learning
- self-supervised learning
- feature engineering
