# LetheSec/Fer2013-Facial-Emotion-Recognition-Pytorch

<https://repo.masters-masters.com/en/repos/LetheSec/Fer2013-Facial-Emotion-Recognition-Pytorch>

[Home](https://repo.masters-masters.com/en) › [LetheSec](https://repo.masters-masters.com/en/owners/LetheSec) › [Fer2013-Facial-Emotion-Recognition-Pytorch](https://repo.masters-masters.com/en/repos/LetheSec/Fer2013-Facial-Emotion-Recognition-Pytorch)

LetheSec/Fer2013-Facial-Emotion-Recognition-Pytorch has 105 stars on GitHub. Its RepoMasters card: Prototype tier. This method achieves SOTA single model…

| Field | Value |
| --- | --- |
| Owner | [LetheSec](https://repo.masters-masters.com/en/owners/LetheSec) |
| Stars | 105 |
| Forks | 18 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2021 |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [LetheSec/Fer2013-Facial-Emotion-Recognition-Pytorch](https://github.com/LetheSec/Fer2013-Facial-Emotion-Recognition-Pytorch) |

## Repository

This method achieves SOTA single model accuracy of 73.70 % on FER2013 without using extra training data.

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.