1 - Pixels to Sentiment: Fine-tuning CNNs for Visual Sentiment Prediction
2 - LeNet
3 - Hypercolumn
This tutorial introduces the LeNet5 neural network architecture using Theano. LeNet5 is a convolutional neural network, good for classifying images. This tutorial shows how to build the architecture, and comes with all the hyper-parameters you need to reproduce the paper's MNIST results.
This implementation simplifies the model in the following ways:
- LeNetConvPool doesn't implement location-specific gain and bias parameters
- LeNetConvPool doesn't implement pooling by average, it implements pooling by max.
- Digit classification is implemented with a logistic regression rather than an RBF network
- LeNet5 was not fully-connected convolutions at second layer
References:
- Y. LeCun, L. Bottou, Y. Bengio and P. Haffner: Gradient-Based Learning Applied to Document Recognition, Proceedings of the IEEE, 86(11):2278-2324, November 1998. http://yann.lecun.com/exdb/publis/pdf/lecun-98.pdf