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CNN Models for Detecting Violence Against Women by Jovi is a document available to read on EtoBox.

This study compares the performance of three pre-trained Convolutional Neural Networks (CNNs) - VGG16, ResNet50, and MobileNet - in detecting physical violence against women in video. Using a dataset of 2,800 images, the MobileNet model achieved the highest accuracy of 89% in classifying violent and non-violent images. The research highlights the potential of deep learning techniques in addressing the critical issue of violence against women through improved surveillance systems.

Author

Jovi

Language

EN