# Gate Recurrent Unit for Efficient Industrial Gas Identification

arXiv: https://arxiv.org/abs/2406.16997 · HTML: https://mlsanity.com/paper/2406.16997/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 9 references that are in the map.
- First posted on arXiv 24 Jun 2024.

## Builds on (most cited first, 1 of 1)

- [Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation](https://mlsanity.com/paper/1406.1078/) (2014)

## Abstract (arXiv)

In recent years, gas recognition technology has received considerable attention. Nevertheless, the gas recognition area has faced obstacles in implementing deep learning-based recognition solutions due to the absence of standardized protocols. To tackle this problem, we suggest a new GRU. Compared to other models, GRU obtains a higher identification accuracy.