Update README.md

README.md

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 # 🧠 FaceGNN v1.1
 
-FaceGNN is a graph-based facial recognition system that combines deep learning feature extraction with Graph Neural Networks (GNNs) for robust identity classification. It supports embedding generation via FaceGNN and offers a reliable system.
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+FaceGNN is a graph-based facial recognition system that combines deep learning feature extraction with Graph Neural Networks (GNNs) for robust secure identity classification. It supports embedding generation through both augmented and non-augmented versions using Graph neural networks. This reliable system has been thoroughly evaluated and consistently demonstrates superior performance, making it well-suited for real-world, high-security applications.
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 ## 📊 Project Overview
 
 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).
-- (3) training and evaluation of a GNN-based classifier.
+-  dataset preparation and embedding generation.
+-  graph construction using k-Nearest Neighbors (k-NN).
+-  training and evaluation of a GNN-based classifier.
 
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