An evaluation of lightweight facial recognition models available in the DeepFace library in clustering tasks - Francisco, Leandro Barbosa da Silva; Marcon, Marlon; Ortoncelli, André Roberto (Anais da Escola Regional de Banco de Dados (ERBD); 2026: Anais da XXI Escola Regional de Banco de DadosDO - 10.5753/erbd.2026.20306, 2026)
This work investigates the use of Deep Learning-based facial recognition models to automatically organize images through unsupervised clustering. We evaluated the FaceNet and ArcFace models using the DeepFace library on a dataset of 100 images of five celebrities. The results show an average accuracy of 92.6%, demonstrating that the choice of model and the clustering algorithm configuration significantly influence performance and enable high accuracy in automatic image organization.