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- ImageNet
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Classroom Contents
ImageNet Classification with Deep Convolutional Neural Networks - Paper Explained
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- 1 - Intro & Overview
- 2 - The necessity of larger models
- 3 - Why CNNs?
- 4 - ImageNet
- 5 - Model Architecture Overview
- 6 - ReLU Nonlinearities
- 7 - Multi-GPU training
- 8 - Classification Results
- 9 - Local Response Normalization
- 10 - Overlapping Pooling
- 11 - Data Augmentation
- 12 - Dropout
- 13 - More Results
- 14 - Conclusion
