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One-Class Classifier for Real Fingerprints

Using the Generative Adversarial Network (GAN), I want to create three (3) separate one-class classifiers for classifying real fingerprints using :

1. The trained discriminator (classifier 1)

2. The trained generator (classifier 2)

3. Both the trained discriminator and generator (classifier 3)

Output (results) of each classifier should show:

1. The classification accuracy

2. A confusion matrix on test data (for each classifier)

3. A graph to compare the level of accuracy for all 3 classifiers created.

4. A 2D t-SNE visualization to display the live and fake fingerprints (for each classifier)

Datasets will be provided.

Also, project should be executed using the [login to view URL] platform.

Compétences : Computer Vision, Machine Learning (ML), Python, Deep Learning, Architecture Logicielle

Concernant le client :
( 1 commentaire ) Shah Alam, Malaysia

Nº du projet : #32704703

Décerné à:


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