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An end-to-end face recognition system using Inception V2 and Triplet Loss for robust embeddings.

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Face Recognition Using Deep Learning 📸🤖

Welcome to the Face Recognition Project, a comprehensive implementation of a face recognition system using deep learning techniques. This project demonstrates the application of neural networks for facial feature encoding and recognition.

🚀 Overview

This project provides an end-to-end implementation of a face recognition system:

  • Face Verification: Determines if two images are of the same person.
  • Face Recognition: Identifies a person from a database of encodings.

Built with TensorFlow, Keras, and Python, it utilizes the Inception V2 architecture and incorporates the Triplet Loss Function for robust feature extraction and comparison.

Acknowledgments 🙌

This project is based on the techniques and methods taught in the Deep Learning Specialization by Andrew Ng. Special thanks to DeepLearning.AI for their exceptional courses and resources.