Deconvolutional networksDeconvolutional networksZeiler, M. D. and Krishnan, D. and Taylor, G. W. and Fergus, R.2010
Paper summaryleopaillier_Objective:_ Define a new deconvolution layer.
#### Results:
Not really interesting except from the fact that it first introduces **deconvolution layers** which are very ill-name as they are not actual deconvolution but instead a **transposed convolution** or also called a **fractionally strided convolutions**.
[![Deconvolutional layer](https://cloud.githubusercontent.com/assets/17261080/25344392/44693b48-2912-11e7-8dda-2b64d99292a9.gif)](https://cloud.githubusercontent.com/assets/17261080/25344392/44693b48-2912-11e7-8dda-2b64d99292a9.gif)
Visualization for other operations can be seen [here](https://github.com/vdumoulin/conv_arithmetic) corresponding to [A guide to convolution arithmetic for deep learning](https://arxiv.org/pdf/1603.07285.pdf).
_Objective:_ Define a new deconvolution layer.
#### Results:
Not really interesting except from the fact that it first introduces **deconvolution layers** which are very ill-name as they are not actual deconvolution but instead a **transposed convolution** or also called a **fractionally strided convolutions**.
[![Deconvolutional layer](https://cloud.githubusercontent.com/assets/17261080/25344392/44693b48-2912-11e7-8dda-2b64d99292a9.gif)](https://cloud.githubusercontent.com/assets/17261080/25344392/44693b48-2912-11e7-8dda-2b64d99292a9.gif)
Visualization for other operations can be seen [here](https://github.com/vdumoulin/conv_arithmetic) corresponding to [A guide to convolution arithmetic for deep learning](https://arxiv.org/pdf/1603.07285.pdf).