Intelligent Identification of MoS2 Nanostructures with Hyperspectral Imaging by 3D-CNN.

ABSTRACT: Increasing attention has been paid to two-dimensional (2D) materials because of their superior performance and wafer-level synthesis methods. However, the large-area characterization, precision, intelligent automation, and high-efficiency detection of nanostructures for 2D materials have not yet reached an industrial level. Therefore, we use big data analysis and deep learning methods to develop a set of visible-light hyperspectral imaging technologies successfully for the automatic identification of few-layers MoS2. For the classification algorithm, we propose deep neural network, one-dimensional (1D) convolutional neural network, and three-dimensional (3D) convolutional neural network (3D-CNN) models to explore the correlation between the accuracy of model recognition and the optical cha

SUBMITTER: Li KC 

PROVIDER: S-EPMC7353172 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature