<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1646-9895</journal-id>
<journal-title><![CDATA[RISTI - Revista Ibérica de Sistemas e Tecnologias de Informação]]></journal-title>
<abbrev-journal-title><![CDATA[RISTI]]></abbrev-journal-title>
<issn>1646-9895</issn>
<publisher>
<publisher-name><![CDATA[AISTI - Associação Ibérica de Sistemas e Tecnologias de Informação]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1646-98952023000100100</article-id>
<article-id pub-id-type="doi">10.17013/risti.49.100-114</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Análisis automático de micrografías SEM mediante aprendizaje profundo]]></article-title>
<article-title xml:lang="en"><![CDATA[Automated analysis of SEM micrographs using deep learning]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Toscano]]></surname>
<given-names><![CDATA[Iker]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Bravo]]></surname>
<given-names><![CDATA[Diego Alejandro Morales]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[De-la-Torre]]></surname>
<given-names><![CDATA[Miguel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Juárez]]></surname>
<given-names><![CDATA[Brenda Acevedo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Mireles]]></surname>
<given-names><![CDATA[Gabriel Alberto García]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Centro Universitario de Los Valles  ]]></institution>
<addr-line><![CDATA[Ameca ]]></addr-line>
<country>México</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad de Guadalajara División de Estudios Científicos y Tecnológicos Departamento de Ciencias Computacionales e Ingenierías]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad de Guadalajara División de Estudios Científicos y Tecnológicos Departamento de Ciencias Naturales y Exactas]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Universidad de Sonora Departamento de Matemáticas ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2023</year>
</pub-date>
<numero>49</numero>
<fpage>100</fpage>
<lpage>114</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_arttext&amp;pid=S1646-98952023000100100&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_abstract&amp;pid=S1646-98952023000100100&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_pdf&amp;pid=S1646-98952023000100100&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El microscopio electrónico de barrido (SEM) es comúnmente utilizado para analizar nanopartículas de distintos materiales y mejorar métodos de fabricación, sistemas de purificación, mejoras en la industria médica, entre otras. En este artículo, se presenta un mapeo sistemático de la literatura referente al uso de técnicas de aprendizaje profundo (AP) para la detección y clasificación de nanopartículas contenidas en micrografías SEM. Los resultados reflejan que las redes neuronales convolucionales (CNN) son las técnicas más utilizadas para analizar micrografías, obteniendo una alta precisión en los proyectos realizados en las publicaciones revisadas. Como prueba de concepto, se presentan ejemplos del uso de los enfoques más comunes en micrografías SEM de CaCO3, incluyendo el uso de herramientas como OpenAI. Los resultados revelan ventajas y retos que se presentan al utilizar técnicas de aprendizaje profundo en el análisis de micrografías SEM.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract The scanning electron microscope (SEM) is commonly used to analyze nanoparticles of different materials and improve manufacturing methods, purification systems, and improve the medical industry, among others. In this article, a systematic mapping of the literature regarding the use of deep learning (AP) techniques for the detection and classification of nanoparticles contained in SEM micrographs is presented. The results reflect those variants of convolutional neural networks (CNN) that are the most widely used techniques to analyze micrographs, obtaining high precision in the projects carried out in the reviewed publications. As proof of concept, examples of the use of the most common approaches in SEM micrographs of CaCO3, including tools like OpenAI, are presented. The results reveal advantages and challenges that arise when using deep learning techniques in the analysis of SEM micrographs.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[aprendizaje profundo]]></kwd>
<kwd lng="es"><![CDATA[micrografías SEM]]></kwd>
<kwd lng="es"><![CDATA[CaCO3]]></kwd>
<kwd lng="es"><![CDATA[nanopartículas]]></kwd>
<kwd lng="es"><![CDATA[redes neuronales convolucionales]]></kwd>
<kwd lng="en"><![CDATA[deep learning]]></kwd>
<kwd lng="en"><![CDATA[SEM micrographs]]></kwd>
<kwd lng="en"><![CDATA[CaCO3]]></kwd>
<kwd lng="en"><![CDATA[nanoparticles]]></kwd>
<kwd lng="en"><![CDATA[convolutional neural networks]]></kwd>
</kwd-group>
</article-meta>
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