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  4. Detection and Classification of Facial Features Through the Use of Convolutional Neural Networks (CNN) in Alzheimer Patients
 
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Detection and Classification of Facial Features Through the Use of Convolutional Neural Networks (CNN) in Alzheimer Patients

Journal
Advances in Intelligent Systems and Computing
Date Issued
2020
Author(s)
Castillo Salazar, David Ricardo
Facultad de Ciencias de la Educación
Varela Aldas, José
Centro de Investigación de Ciencias Humanas y de la Educación
Borja M.
Guevara Maldonado, César Byron
Centro de investigación en Mecatrónica y Sistemas Interactivos
Arias Flores, Hugo Patricio
Centro de investigación en Mecatrónica y Sistemas Interactivos
Fierro-Saltos W.
Rivera R.
Hidalgo-Guijarro J.
Yandún-Velasteguí M.
Lanzarini L.
Alvarado H.G.
Type
Conference Paper
DOI
10.1007/978-3-030-27928-8_94
URL
https://cris.indoamerica.edu.ec/handle/123456789/8931
Abstract
In recent years, the widespread use of artificial neural networks in the field of image processing has been of vital relevance to research. The main objective of this research work is to present an effective and efficient method for the detection of eyes, nose and lips in images that include faces of Alzheimer’s patients. The methods to be used are based on the extraction of deep features from a well-designed convolutional neural network (CNN). The result focuses on the processing and detection of facial features of people with and without Alzheimer’s disease. © Springer Nature Switzerland AG 2020.
Subjects
  • Assistive technologie...

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