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Recent advances on effective and efficient deep learning-based solutions

This editorial briefly analyses, describes, and provides a short summary of a set of selected papers published in a special issue focused on deep learning methods and architectures and their application to several domains and research areas. The set of selected and published articles covers several...

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Detalles Bibliográficos
Autores principales: Martín, Alejandro, Camacho, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer London 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9131985/
https://www.ncbi.nlm.nih.gov/pubmed/35637932
http://dx.doi.org/10.1007/s00521-022-07344-9
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author Martín, Alejandro
Camacho, David
author_facet Martín, Alejandro
Camacho, David
author_sort Martín, Alejandro
collection PubMed
description This editorial briefly analyses, describes, and provides a short summary of a set of selected papers published in a special issue focused on deep learning methods and architectures and their application to several domains and research areas. The set of selected and published articles covers several aspects related to two basic aspects in deep learning (DL) methods, efficiency of the models and effectiveness of the architectures These papers revolve around different interesting application domains such as health (e.g. cancer, polyps, melanoma, mental health), wearable technologies solar irradiance, social networks, cloud computing, wind turbines, object detection, music, and electricity, among others. This editorial provides a short description of each published article and a brief analysis of their main contributions.
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spelling pubmed-91319852022-05-26 Recent advances on effective and efficient deep learning-based solutions Martín, Alejandro Camacho, David Neural Comput Appl Editorial This editorial briefly analyses, describes, and provides a short summary of a set of selected papers published in a special issue focused on deep learning methods and architectures and their application to several domains and research areas. The set of selected and published articles covers several aspects related to two basic aspects in deep learning (DL) methods, efficiency of the models and effectiveness of the architectures These papers revolve around different interesting application domains such as health (e.g. cancer, polyps, melanoma, mental health), wearable technologies solar irradiance, social networks, cloud computing, wind turbines, object detection, music, and electricity, among others. This editorial provides a short description of each published article and a brief analysis of their main contributions. Springer London 2022-05-25 2022 /pmc/articles/PMC9131985/ /pubmed/35637932 http://dx.doi.org/10.1007/s00521-022-07344-9 Text en © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Editorial
Martín, Alejandro
Camacho, David
Recent advances on effective and efficient deep learning-based solutions
title Recent advances on effective and efficient deep learning-based solutions
title_full Recent advances on effective and efficient deep learning-based solutions
title_fullStr Recent advances on effective and efficient deep learning-based solutions
title_full_unstemmed Recent advances on effective and efficient deep learning-based solutions
title_short Recent advances on effective and efficient deep learning-based solutions
title_sort recent advances on effective and efficient deep learning-based solutions
topic Editorial
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9131985/
https://www.ncbi.nlm.nih.gov/pubmed/35637932
http://dx.doi.org/10.1007/s00521-022-07344-9
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