An improved CNN-based methodology to prevent risky situations in people by recognizing emotions from facial features

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Authors: José Félix Serrano Talamantes, Mauricio Olguín Carbajal, Gerardo Miramontes-de Léon, Héctor Durán Muñoz, Claudia Sifuentes-Gallardo, Carlos Aviles Cruz, Gabriel de Jesús Celis-Escudero
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Abstract

This proposal shows a methodology designed for the process of detecting emotions through facial features. The process of facial features detection involves several stages among which the most important ones are: Acquisition of the training set of images, detection and segmentation of the face using face location techniques in images using Viola & Jones algorithm. We also make use of neural networks that are part of Deep Learning techniques. In this way we propose to recognize people’s faces and also perceive their emotions through gestures that are captured by means of a camera, allowing us to obtain these in soft real time. The processes of this methodology were developed and programmed in the MATLAB and Python code. There was a significant improvement in the recognition results throughout the CNN. Smart citations: https://scite.ai/reports/10.61467/2007.1558.2026.v17i2.1261Dimensions.Open Alex.

Fields of Study & Subjects

Emotion and Mood Recognition Face recognition and analysis Face and Expression Recognition

Publication details

Journal / source
International Journal of Combinatorial Optimization Problems and Informatics.
Volume
17
Issue
2
Pages
89–101
Publication date
16 February 2026
Language
EN