Pattern Recognition and Deep Learning Technologies, Enablers of Industry 4.0, and Their Role in Engineering Research
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Archivos
Fecha
2023-02
Profesor/a Guía
Facultad/escuela
Idioma
en
Título de la revista
ISSN de la revista
Título del volumen
Editor
MDPI
Nombre de Curso
Licencia CC
CC BY 4.0 Attribution 4.0 International Deed
Licencia CC
https://creativecommons.org/licenses/by/4.0/
Resumen
The purpose of this study is to summarize the pattern recognition (PR) and deep learning (DL) artificial intelligence methods developed for the management of data in the last six years. The methodology used for the study of documents is a content analysis. For this study, 186 references are considered, from which 120 are selected for the literature review. First, a general introduction to artificial intelligence is presented, in which PR/DL methods are studied and their relevance to data management evaluated. Next, a literature review is provided of the most recent applications of PR/DL, and the capacity of these methods to process large volumes of data is evaluated. The analysis of the literature also reveals the main applications, challenges, approaches, advantages, and disadvantages of using these methods. Moreover, we discuss the main measurement instruments; the methodological contributions by study areas and research domain; and major databases, journals, and countries that contribute to the field of study. Finally, we identify emerging research trends, their limitations, and possible future research paths. © 2023 by the authors.
Notas
Indexación: Scopus
Palabras clave
Artificial Intelligence, Data Management, Deep Learning, Pattern Recognition
Citación
Symmetry. Volume 15, Issue 2. February 2023. Article number 535
DOI
10.3390/sym15020535