# LahiruJayasinghe/RUL-Net

<https://repo.masters-masters.com/en/repos/LahiruJayasinghe/RUL-Net>

[Home](https://repo.masters-masters.com/en) › [LahiruJayasinghe](https://repo.masters-masters.com/en/owners/LahiruJayasinghe) › [RUL-Net](https://repo.masters-masters.com/en/repos/LahiruJayasinghe/RUL-Net)

LahiruJayasinghe/RUL-Net has 251 stars on GitHub. Its RepoMasters card: Alpha tier. Deep learning approach for estimation of Remaining Useful Life (RUL) of an…

| Field | Value |
| --- | --- |
| Owner | [LahiruJayasinghe](https://repo.masters-masters.com/en/owners/LahiruJayasinghe) |
| Stars | 251 |
| Forks | 70 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2018 |
| Topics | augmentaiton, remaining-useful-life, sensor-fusion, 1d-convolution, lstm-cnn, regression, long-short-term-memory, convolutional-neural-networks |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [LahiruJayasinghe/RUL-Net](https://github.com/LahiruJayasinghe/RUL-Net) |

## Repository

Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine

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.