Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Recolector de Cienci...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Recolector de Ciencia Abierta, RECOLECTA
Bachelor thesis . 2021
License: CC BY NC ND
versions View all 2 versions
addClaim

Estudio de detección de emociones a través de reconocimiento de características faciales con técnicas AI

Study of Emotion Detection Through Facial Feature Recognition with AI Techniques
Authors: Moreno Urrea, Francisco Alfredo;

Estudio de detección de emociones a través de reconocimiento de características faciales con técnicas AI

Abstract

El objetivo de este TFG es conocer y aplicar, de forma práctica, técnicas de reconocimiento de emociones mediante el reconocimiento facial usando modelos de AI, propios y/o mejorados. Resumen de la Oferta: Una de los medios más importantes empleado por los humanos para mostrar sus emociones es a través de las expresiones faciales. Así, el reconocimiento de la expresión facial es uno de los medios más poderosos, naturales e inmediatos para que los seres humanos comuniquen sus emociones e intenciones. El reconocimiento automático de las emociones humanas ha recibido mucha atención recientemente con la introducción del IoT y los ambientes inteligentes. Es sabido además, que el uso del procesamiento del lenguaje natural para comunicarse con los humanos, cuando se incrementa con las emociones, aumenta el nivel de comunicación efectiva y la inteligencia a nivel humano. Dado el interés que despierta este área, el objetivo de este TFG será aprender cómo funcionan los sistemas de detección de emociones basadas en el reconocimiento de características faciales mediante el empleo de técnicas de Inteligencia Artificial (AI) y emplarlos de forma práctica.

Escuela Técnica Superior de Ingeniería de Telecomunicación

Universidad Politécnica de Cartagena

Country
Spain
Related Organizations
Keywords

Ingeniería Telemática, Artificial intelligence, 3325 Tecnología de las Telecomunicaciones, Inteligencia artificial

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
Related to Research communities