Face Recognition using CNN and Amazon S3: An Expandable and Safe Integration for Various Uses

Lately, there has been notable interest in utilizing Convolutional Neural Networks (CNN) for face recognition, underlining its significance and relevance., finding utility in diverse areas such as security systems, personal device authentication, and social media tagging. This abstract presents an implementation of a CNN-based face recognition algorithm that effectively leverages data stored within an Amazon S3 bucket. The CNN model’s primary objective is the precise identification and categorization of human faces within the stored dataset, harnessing the inherent capabilities of CNNs for extracting and classifying facial features. The system’s efficiency is greatly enhanced by the scalability and accessibility provided by Amazon S3 storage, underscoring the seamless integration of cutting-edge machine learning techniques with a cloud-based storage infrastructure. This solution demonstrates a powerful and adaptable framework for face recognition applications, encompassing various potential use cases ranging from security and authentication to personalized user experiences.