# MENGLAN: Multiscale Enhanced Nonparametric Gas Analyzer with Lightweight Architecture and Networks

arXiv: https://arxiv.org/abs/2506.22490 · HTML: https://mlsanity.com/paper/2506.22490/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 18 references that are in the map.
- First posted on arXiv 24 Jun 2025.

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

- [DEA-Net: Single image dehazing based on detail-enhanced convolution and content-guided attention](https://mlsanity.com/paper/2301.04805/) (2023)

## Abstract (arXiv)

Accurate detection of ethylene concentrations in mixed gases is crucial in chemical production for safety and health purposes. Traditional methods are hindered by high cost and complexity, limiting their practical application. This study proposes MENGLAN, a Multiscale Enhanced Nonparametric Gas Analyzer that integrates a dual-stream structure, a Hybrid Multi-Head Attention mechanism, and a Feature Reactivation Module to enable real-time, lightweight, and high-precision ethylene concentration prediction. Results show that MENGLAN achieves superior performance, reduced computational demand, and enhanced deployability compared to existing methods.