Special Issue "Artificial Neural Networks: Design and Applications"
Deadline for manuscript submissions: 31 October 2022 | Viewed by 1499
Interests: artificial intelligence; machine learning; neuromorphic computing
Interests: neuromorphic computing; deep learning; speech recognition
Deep learning, a major driving force behind artificial neural networks, has achieved remarkable progress in the field of image recognition, speech processing, machine translation, and board games. In particular, deep learning has drastically outperformed traditional methods and overtaken them to become the choice in different applications. However, many traditional network structures may not be able to deal with the increasing challenges of modern complex tasks, especially on non-structural data and complicated decision-making problems. To resolve this problem, various neural network structures and algorithms have been proposed in recent years, such as graph neural networks, spiking neural networks, and deep reinforcement learning. This Special Issue will focus on state-of-the-art neural network models, innovative learning methods, and applications. We seek contributions that include but are not limited to:
- Graph neural networks
- Deep neural networks
- Spiking neural networks
- Computer vision
- Natural language processing
- Bayesian methods
- Multi-agent reinforcement learning
- Brain-inspired artificial neural networks
Prof. Dr. Hong Qu
Dr. Malu Zhang
Dr. Mingsheng Fu
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. Mathematics 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 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.
- graph neural networks
- deep neural networks
- spiking neural networks
- computer vision
- natural language processing
- bayesian methods
- multi-agent reinforcement learning
- brain-inspired artificial neural networks