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Diffstat (limited to 'tensorflow/docs_src/tutorials/deep_cnn.md')
| -rw-r--r-- | tensorflow/docs_src/tutorials/deep_cnn.md | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/tensorflow/docs_src/tutorials/deep_cnn.md b/tensorflow/docs_src/tutorials/deep_cnn.md index 591b8ea6aa..b57ef24f58 100644 --- a/tensorflow/docs_src/tutorials/deep_cnn.md +++ b/tensorflow/docs_src/tutorials/deep_cnn.md @@ -11,8 +11,8 @@ problem is to classify RGB 32x32 pixel images across 10 categories: airplane, automobile, bird, cat, deer, dog, frog, horse, ship, and truck. ``` -For more details refer to the [CIFAR-10 page](http://www.cs.toronto.edu/~kriz/cifar.html) -and a [Tech Report](http://www.cs.toronto.edu/~kriz/learning-features-2009-TR.pdf) +For more details refer to the [CIFAR-10 page](https://www.cs.toronto.edu/~kriz/cifar.html) +and a [Tech Report](https://www.cs.toronto.edu/~kriz/learning-features-2009-TR.pdf) by Alex Krizhevsky. ### Goals @@ -42,7 +42,7 @@ designing larger and more sophisticated models in TensorFlow: ([wiki](https://en.wikipedia.org/wiki/Convolutional_neural_network#Pooling_layer)) and @{tf.nn.local_response_normalization$local response normalization} (Chapter 3.3 in -[AlexNet paper](http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf)). +[AlexNet paper](https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf)). * @{$summaries_and_tensorboard$Visualization} of network activities during training, including input images, losses and distributions of activations and gradients. |