A Comparative Study of Three Pre-trained Convolutional Neural Networks in the Detection of Violence Against Women

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Ivan Gaytán Aguilar http://orcid.org/0000-0002-4101-5351
Alejandro Aguilar Contreras http://orcid.org/0000-0003-1493-2987
Roberto Alejo Eleuterio http://orcid.org/0000-0002-7580-3305
Eréndira Rendón Lara http://orcid.org/0000-0003-4581-6022
Grisel Miranda Piña http://orcid.org/0000-0001-7122-0658
Everardo E. Granda Guitérrez http://orcid.org/0000-0002-9316-9627

Resumen

Se presenta una comparación de rendimiento entre tres modelos de redes CNN preentrenadas (VGG16, ResNet50 y MobileNet) en la detección en video de violencia física contra la mujer. Para llevar a cabo la clasificación de imágenes que incluyan violencia física contra la mujer y aquellas que no, se recolectaron 2 800 imágenes (1 400 violentas y 1 400 no violentas) de un Dataset público y posteriormente fueron divididas en entrenamiento (1 200 imágenes), validación (1 000 imágenes) y prueba (600 imágenes). Para evaluar su rendimiento, se tomaron en cuenta los valores de exactitud para cada modelo; al respecto, la red MobileNet se posiciona como el clasificador con mejor rendimiento para esta tarea de clasificación con 89% de exactitud.

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Como citar
GAYTÁN AGUILAR, Ivan et al. A Comparative Study of Three Pre-trained Convolutional Neural Networks in the Detection of Violence Against Women. CIENCIA ergo-sum, [S.l.], v. 31, abr. 2023. ISSN 2395-8782. Disponible en: <https://cienciaergosum.uaemex.mx/article/view/19352>. Fecha de acceso: 21 jul. 2024 doi: https://doi.org/10.30878/ces.v31n0a17.
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