Comparing End-to-End Machine Learning Methods for Spectra Classification
Dec 5, 2021 · This study aims to develop deep learning (DL) classification frameworks for one-dimensional (1D) spectral time series. In this work, we deal with the spectra classification problem …
Machine Learning Applied for Spectra Classification
Sep 10, 2021 · In this work, we apply recent popular machine learning/deep learning models to HED experimental spectra data classification. The models we presented range from supervised deep …
Interpretable machine learning models classify minerals via ...
May 6, 2025 · Here, we developed interpretable machine learning models that can classify uranium minerals by secondary oxyanion chemistry and other physicochemical properties based solely on …
Validating neural networks for spectroscopic classification on a ...
Jun 5, 2023 · To aid the development of machine learning models for automated spectroscopic data classification, we created a universal synthetic dataset for the validation of their performance.
Machine learning prediction of UV–Vis spectra features of organic ...
Dec 9, 2021 · Machine learning (ML) algorithms were explored for the classification of the UV–Vis absorption spectrum of organic molecules based on molecular descriptors and fingerprints generated …
A machine learning based classification models for plastic recycling ...
Nov 10, 2022 · In this study, we proposed a methodology for plastic classification in which the comparative performance of different machine learning models was analyzed to identify spectra …
Performance of machine learning classification models of ... - Springer
Jul 24, 2020 · Autism spectrum disorders (ASDs) are heterogeneous neurodevelopmental conditions. In fMRI studies, including most machine learning studies seeking to distinguish ASD from typical …
Classification and Feature Selection of Autism Spectrum ... - Springer
Mar 13, 2025 · Univariate neuroimaging studies have shown brain differences in individuals with autism spectrum disorder (ASD) compared to healthy controls (CTL). In contrast, together with …
Machine learning classification of autism spectrum disorder based …
We used existing open-source computer vision algorithms for objective annotation to extract information based on the synchrony of movement and facial expression. These were subsequently used as …
Machine learning in spectral domain - Nature Communications
Feb 26, 2021 · Theoretical aspects of automated learning from data involving deep neural networks have open questions. Here Giambagli et al. show that training the neural networks in the spectral …