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Rotated MNIST data and a shallow CNN achieves 99.48% accuracy, using a core i7 CPU and 1.5 hours of training!

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Rotated_MNIST

Rotated MNIST data and a shallow CNN achieves 99.48 % accuracy in less than 1 hour, using a core-i7 CPU machine (no GPU)! The result is as good as this google paper but the model is much simpler. https://papers.nips.cc/paper/5854-spatial-transformer-networks.pdf

You can run the test.py to test the saved model

For testing you just need keras; for training openCV (cv2), imutils and keras are required

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Rotated MNIST data and a shallow CNN achieves 99.48% accuracy, using a core i7 CPU and 1.5 hours of training!

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