Aprendizaje profundo para clasificación de nanopartículas en micrografías SEM: mapeo sistemático

Iker Toscano, Miguel De-La-Torre, Brenda Acevedo Juárez, Gabriel Alberto García Mireles

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

In recent years the microscopy industry has had significant technological advances.Today these advances allow us to obtain micrographs taken by microscopes with a high resolution at very small scales that allow us to observe nanoparticles, an example of this is the scanning electron microscope (SEM). The analysis of nanoparticles contained within these micrographs is necessary in order to improve manufacturing methods, purification systems, improvements in the medical industry, among others. In this article, a systematic mapping study of the literature on the use of deep learning techniques for the detection and classificationof nanoparticles contained in SEM micrographs is presented. An analysis is made of the main neural networks used and the methods implemented for the generation of an input training database for the neural networks. Results show that convolutional neural networks (CNN) are themost common techniques to analyze micrographs, obtaining a high accuracy in the projects developed in the reviewed publications.In order to create a framework and methodology that allows us to detect, classify and count, the mapping study allows us to identify the most efficient technologies to develop systems capable of performing these tasks in an automated way with the help of deep learning.

Título traducido de la contribuciónDeep Learning for Nanoparticle Classification in SEM Micrographs: Systematic Mapping
Idioma originalEspañol
Título de la publicación alojadaApplications in Software Engineering - Proceedings of the 11th International Conference on Software Process Improvement, CIMPS 2022
EditoresJezreel Mejia Miranda, Jair de Jesus Cambon Navarrete, Juan Ramon Nieto Quezada
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas119-125
Número de páginas7
ISBN (versión digital)9798350398960
DOI
EstadoPublicada - 2022
EventoApplications in Software Engineering - 11th International Conference on Software Process Improvement, CIMPS 2022 - Acapulco, Guerrero, México
Duración: 19 oct. 202221 oct. 2022

Serie de la publicación

NombreApplications in Software Engineering - Proceedings of the 11th International Conference on Software Process Improvement, CIMPS 2022

Conferencia

ConferenciaApplications in Software Engineering - 11th International Conference on Software Process Improvement, CIMPS 2022
País/TerritorioMéxico
CiudadAcapulco, Guerrero
Período19/10/2221/10/22

Nota bibliográfica

Publisher Copyright:
© 2022 IEEE.

Palabras clave

  • Micrograp
  • SEM
  • Scanning electron microscope
  • deep learning
  • nanoparticles

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