https://github.com/ranimeshehata/face-recognition
This project implements a face recognition pipeline using the AT&T Face Dataset (ORL Dataset). It includes dimensionality reduction techniques like PCA, clustering algorithms such as K-Means and GMM, and an optional Autoencoder-based feature extraction.
https://github.com/ranimeshehata/face-recognition
autoencoders cnn dimensionality-reduction face-recognition gmm-clustering kmeans-clustering machine-learning opencv pca python
Last synced: 2 months ago
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This project implements a face recognition pipeline using the AT&T Face Dataset (ORL Dataset). It includes dimensionality reduction techniques like PCA, clustering algorithms such as K-Means and GMM, and an optional Autoencoder-based feature extraction.
- Host: GitHub
- URL: https://github.com/ranimeshehata/face-recognition
- Owner: ranimeshehata
- Created: 2025-04-20T11:46:54.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-05-01T07:17:20.000Z (about 1 year ago)
- Last Synced: 2026-05-02T11:41:53.169Z (2 months ago)
- Topics: autoencoders, cnn, dimensionality-reduction, face-recognition, gmm-clustering, kmeans-clustering, machine-learning, opencv, pca, python
- Language: Jupyter Notebook
- Homepage:
- Size: 19.2 MB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0