# ai-med/squeeze\_and\_excitation

<https://repo.masters-masters.com/en/repos/ai-med/squeeze_and_excitation>

[Home](https://repo.masters-masters.com/en) › [ai-med](https://repo.masters-masters.com/en/owners/ai-med) › [squeeze\_and\_excitation](https://repo.masters-masters.com/en/repos/ai-med/squeeze_and_excitation)

ai-med/squeeze\_and\_excitation has 321 stars on GitHub. Its RepoMasters card: Alpha tier. PyTorch Implementation of 2D and 3D 'squeeze and excitation' blocks…

| Field | Value |
| --- | --- |
| Owner | [ai-med](https://repo.masters-masters.com/en/owners/ai-med) |
| Stars | 321 |
| Forks | 52 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2018 |
| Topics | deep-learning, segmentation, squeeze-and-excitation, convolutional-networks, pytorch, fully-convolutional-networks |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [ai-med/squeeze\_and\_excitation](https://github.com/ai-med/squeeze_and_excitation) |

## Repository

PyTorch Implementation of 2D and 3D 'squeeze and excitation' blocks for Fully Convolutional Neural Networks

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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