Emerging Trends of Deep Learning in AI: Challenges and Methodologies
A special issue of AI (ISSN 2673-2688).
Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 7880
Special Issue Editors
2. Deep Learning & Data Science Division, Capacloud AI, Kolkata 711103, India
Interests: computational material science; computational mechanics; condensed matter physics; computer vision; deep learning; generative adversarial networks; object detection; brain–machine interface
Special Issue Information
Dear Colleagues,
The last decade has seen the increasingly important, even dominant, application of deep learning (DL) in the field of various applications. Conventional machine learning methods have been the focus of intense investigations for years; however, they have limited capabilities, are biased to dataset selection, and are faced with an overwhelming challenge to integrate large, heterogeneous data sources. On the other hand, recent advancements in deep learning architectures, coupled with high-performance computing, have demonstrated significant breakthroughs in dealing with complexities by radically changing research methodologies toward a data-oriented approach.
This Special Issue encourages authors, from academia and industry, to submit new research results about positioning and navigation models based on machine learning for complex systems. The Special Issue topics include but are not limited to the following:
- Artificial neural networks;
- Convolutional neural networks;
- Recurrent neural network;
- Deep reinforcement learning;
- Generative adversarial network;
- Attention-based transformer;
- Computer vision;
- Vision transformer;
- Object detection;
- Image segmentation;
- Brain–machine interface.
Dr. Arunabha Mohan Roy
Dr. Jayabrata Bhaduri
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. AI is an international peer-reviewed open access quarterly 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 1600 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
- machine learning
- artificial intelligence
- big data
- complex system
