Ingeniería de software

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Ingeniero de Software
(Universidad Católica de Cuenca., 2023) Tenesaca Pesantez, Jorge Andres; Yanza Saca, Gustavo Xavier; Quevedo Sacoto, Andrés Sebastián; 0150294098; 0105091029
In this project, face recognition, an essential component of interpersonal identification throughout history, has been explored, with the advancement of artificial intelligence and deep learning, a face recognition microservice was developed based on advanced algorithms, specifically using FaceNet-PyTorch. This approach overcomes the limitations of traditional methods, providing greater accuracy and adaptability in real-world situations, the microservices architecture offers modularity and scalability, while cosine similarity analysis on facial representations optimizes data management, overall, this project provides an effective and versatile solution for facial recognition, with potential to impact a wide range of applications.