Creation of a Deep Convolutional Auto-Encoder in Caffe

Understand

The development of a deep (stacked) convolutional auto-encoder in the Caffe deep learning framework is presented in this paper.

• We describe simple principles which we used to create this model in Caffe.
• The proposed model of convolutional auto-encoder does not have pooling/unpooling layers yet.
• The results of our experimental research show comparable accuracy of dimensionality reduction in comparison with a classic auto-encoder on the example of MNIST dataset.