# Creation of a Deep Convolutional Auto-Encoder in Caffe

arXiv: https://arxiv.org/abs/1512.01596 · HTML: https://mlsanity.com/paper/1512.01596/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Dec 2015.

## Built on by (most cited first, 1 of 1)

- [Mitigating Data Absence in Federated Learning Using Privacy-Controllable Data Digests](https://mlsanity.com/paper/2210.00737/) (2022)

## Abstract (arXiv)

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.