An interpretable and transferrable vision transformer model for rapid materials spectra classification
Zhenru Chen, Yunchao Xie, Yuchao Wu, Yuyi Lin, Shigetaka Tomiya, Jian Lin
Abstract
An interpretable and transferrable Vision Transformer (ViT) model was developed for classifying individual materials from their XRD and FTIR spectra.
Topics & Concepts
TransformerArtificial intelligenceComputer scienceSpectral linePattern recognition (psychology)Machine learningEngineeringElectrical engineeringPhysicsVoltageAstronomyMachine Learning in Materials ScienceAdvanced Chemical Sensor TechnologiesSpectroscopy and Chemometric Analyses