Selective denoising autoencoder for classification of noisy gas mixtures using 2D transition metal dichalcogenides.

Electronic nose (E-nose) technology, which is composed of an array of chemical sensors and pattern recognition, has been widely utilized for the quantitative classification of gas mixtures. However, for the practical use of E-nose in real-industry, advanced algorithms are necessary to handle the noise in sensing data caused by various environmental variables. In order to achieve precise measurements even in real-world environments, it is necessary to denoise and classify noisy sensing data.