# DIAGNijmegen/StreamingCNN

<https://repo.masters-masters.com/en/repos/DIAGNijmegen/StreamingCNN>

[Home](https://repo.masters-masters.com/en) › [DIAGNijmegen](https://repo.masters-masters.com/en/owners/DIAGNijmegen) › [StreamingCNN](https://repo.masters-masters.com/en/repos/DIAGNijmegen/StreamingCNN)

DIAGNijmegen/StreamingCNN has 101 stars on GitHub. Its RepoMasters card: Prototype tier. To train deep convolutional neural networks, the input data and the…

| Field | Value |
| --- | --- |
| Owner | [DIAGNijmegen](https://repo.masters-masters.com/en/owners/DIAGNijmegen) |
| Stars | 101 |
| Forks | 26 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | MIT |
| Created | 2018 |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [DIAGNijmegen/StreamingCNN](https://github.com/DIAGNijmegen/StreamingCNN) |

## Repository

To train deep convolutional neural networks, the input data and the activations need to be kept in memory. Given the limited memory available in current GPUs, this limits the maximum dimensions of the input data. Here we demonstrate a method to train convolutional neural networks while holding only…

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.