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

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Book cover Human Systems Engineering and Design II (IHSED 2019)

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.

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Correspondence to David Castillo-Salazar .

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Castillo-Salazar, D. et al. (2020). Detection and Classification of Facial Features Through the Use of Convolutional Neural Networks (CNN) in Alzheimer Patients. In: Ahram, T., Karwowski, W., Pickl, S., Taiar, R. (eds) Human Systems Engineering and Design II. IHSED 2019. Advances in Intelligent Systems and Computing, vol 1026. Springer, Cham. https://doi.org/10.1007/978-3-030-27928-8_94

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