Special Issue "Deep Learning, Reconfigurable Computing, and Machine Learning in Healthcare"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 10 April 2021.

Special Issue Editor

Prof. Dr. Rui Pedro Lopes
Website
Guest Editor
Research Center in Digitalization and Industrial Robotics, Instituto Politécnico de Bragança, 5300-253 Bragança, Portugal
Interests: deep learning; machine learning; distributed systems; natural language processing

Special Issue Information

Dear Colleagues,

The machine learning research community has been constantly evolving since Artificial Intelligence was founded as an academic discipline in the 1950s. Through several ups, with the development of information theory in the 1960s, with the comeback of neural networks in the 1990s, and the development of deep learning in this decade; as well as downs, with the barrier of limited processing and storage capacities in the 1970s, and with the disappointing results and the collapse of dedicated hardware vendors in the early 2000; the latest developments and research on deep learning, dedicated hardware, big data, and high-speed networks has been achieving astonishing results. Machine learning, and in particular, the deep learning subfield, has receiving an extraordinary attention in both the scientific and professional communities. It is being applied in many areas of human knowledge, such as medicine, economics, education, and manufacturing. The combination of large datasets, with powerful computer vision, pattern recognition, and text analysis algorithms, enables us to develop practical solutions in a variety of intelligent software and applications. These successes only seem to accelerate, with new algorithms, faster hardware, and carefully annotated datasets appearing every day.

The aim of this Special Issue is to provide researchers and professionals with high-quality research papers addressing the latest advances in the following domains: machine learning, deep learning, dedicated accelerator hardware, and reconfigurable computing.

Prof. Dr. Rui Pedro Lopes
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. Electronics 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

  • neural networks
  • deep learning
  • convolutional neural networks
  • reconfigurable computing
  • near-data processing
  • parallelization

Published Papers

This special issue is now open for submission.
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