Special Issue "Applied Artificial Neural Networks"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 31 July 2020.

Special Issue Editor

Dr. Marcos Gestal
E-Mail Website
Guest Editor
Computation Sciences and Information Technologies Department, Faculty of Computer Science, University of A Coruña, 15071, A Coruña, Spain
Interests: Evolutionary Computation; Artificial Neural Networks; Artificial Intelligence; Feature Selection; Machine Learning

Special Issue Information

Dear Colleagues,

Over the years, there have been many attempts to understand, and subsequently imitate, the way humans try to solve problems, in order to help achieve the same kind of intelligent behavior.

Among these attempts, one of them has been especially successful: artificial neural networks, which simplify the functioning of one of the most complex organs in Nature: the brain. Through the interconnection of nodes and a learning process from examples, these networks provide excellent solutions in a diverse range of fields of research.

After overcoming a small bump in recent years, they have been revived under the name of Deep Neural Networks, which have the same basis and take advantage of the emergence of new learning algorithms and greater computational capabilities.

This Special Issue aims to accommodate, on the one hand, the latest theoretical advances in this field, such as new learning paradigms or new architectures, and, on the other hand, those more recent works in the scientific field where the authors have used any of the many types of available neural networks to reach the best results in their area(s): image or video processing, pattern recognition, forecasting, time-series processing, real-time decision systems, etc.

We kindly invite researchers and investigators to contribute their original research or review articles to this Special Issue.

Dr. Marcos Gestal
Guest Editor

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 papers will be 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. Applied Sciences 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.

Keywords

  • artficial neural networks
  • deep neural networks
  • deep learning
  • machine learning
  • pattern matching
  • artificial intelligence
  • learning algorithms
  • applications

Published Papers

This special issue is now open for submission.
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