Advantages of Transfer Learning

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Table of contents

1 Description of the problem
2 Literature Review
2.1 SIFT
2.2 Convolutional Neural Network and Transfer Learning
2.3 Auto-encoder
3 Description and tuning of the models
3.1 Naive Approach
3.2 Classic Approach
3.2.1 First experiment with dropouts
3.2.2 Data Augmentation
3.2.3 Sensitivity of the results
3.3 Approach with auto-encoders
3.3.1 Description of the model
3.3.2 Results
4 Comparison of the three approaches
5 Annexes