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This study proposes a novel approach for face recognition by leveraging Graph Neural Networks (GNNs) to classify face embeddings extracted from face images. The methodology comprises three main phases: (1) dataset preparation and embedding generation, (2) graph construction using k-Nearest Neighbors (k-NN), and (3) training and evaluation of a GNN-based classifier.

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