Álvarez-Pato, Víctor M.
Preferred name
Álvarez-Pato, Víctor M.
Official Name
Álvarez Pato, Víctor Manuel
Alternative Name
valvarez
Main Affiliation
ORCID
0000-0002-4621-7091
Scopus Author ID
57204802695
Researcher ID
ELA-8147-2022
8 results
Now showing 1 - 8 of 8
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Item type:Publication, Estrategia de dificultad adaptativa para un videojuego de dos jugadores(2013)Maestría en Ciencias - Tesis presentada en UP Aguascalientes16 185 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, 12 2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, 7 2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Consumer Acceptances Through Facial Expressions of Encapsulated Flavors Based on a Nanotechnology Approach(2018); ; ; Scopus© Citations 2 10 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Evaluación de reacciones emocionales a productos alimenticios por medio de reconocimiento automático de expresiones faciales(2022-06)Las emociones son mecanismos que los seres vivos más complejos han desarrollado a lo largo de millones de años de evolución. Como tales, forman parte integral del ser humano y afectan su comportamiento, muchas veces de manera inconsciente pero determinante. Suelen presentarse acompañadas de manifestaciones fisiológicas entre las que se cuentan las expresiones faciales, cambios en el ritmo cardiaco y la respuesta galvánica de la piel. En esta tesis desarrollamos un sistema basado en redes neuronales convolucionales para interpretar expresiones faciales. También utilizamos otros algoritmos de inteligencia artificial para estudiar señales biométricas y determinar qué tan útiles pueden resultar para entender las emociones de una persona y eventualmente predecir sus reacciones a ciertos alimentos, lo que puede resultar de capital importancia en el desarrollo de este tipo de productos. La red neuronal resultante muestra resultados equiparables a los obtenidos en estudios similares por medio de software comercial y los análisis realizados arrojan luz sobre el papel que pueden desempeñar las mediciones de ritmo cardiaco, respuesta galvánica y expresiones faciales en este tipo de investigaciones.71 156 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Multisensor Data Fusion Approach for Predicting Consumer Acceptance of Food Products(2020); ; ; ; <jats:p>Sensory experiences play an important role in consumer response, purchase decision, and fidelity towards food products. Consumer studies when launching new food products must incorporate physiological response assessment to be more precise and, thus, increase their chances of success in the market. This paper introduces a novel sensory analysis system that incorporates facial emotion recognition (FER), galvanic skin response (GSR), and cardiac pulse to determine consumer acceptance of food samples. Taste and smell experiments were conducted with 120 participants recording facial images, biometric signals, and reported liking when trying a set of pleasant and unpleasant flavors and odors. Data fusion and analysis by machine learning models allow predicting the acceptance elicited by the samples. Results confirm that FER alone is not sufficient to determine consumers’ acceptance. However, when combined with GSR and, to a lesser extent, with pulse signals, acceptance prediction can be improved. This research targets predicting consumer’s acceptance without the continuous use of liking scores. In addition, the findings of this work may be used to explore the relationships between facial expressions and physiological reactions for non-rational decision-making when interacting with new food products.</jats:p>Scopus© Citations 41 18 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Method for Facial Emotion Recognition Based on Interest Points(2018); ; Gutiérrez, SebastiánScopus© Citations 15 42 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Facial Emotion Recognition: A Comparison of Different Landmark-Based Classifiers(2018); ; ; Scopus© Citations 18 39 2