A novel deep learning-based chemical image identification method of infrared spectroscopy using external perturbation†
Abstract
Perturbation-induced infrared spectroscopy combined with a deep learning-based chemical image identification method is proven to enable rapid and non-destructive identification of samples of different classes with a quite similar composition and morphological complexity with experimental validation. This study is significant for implementing advanced technology in the field of deep learning to solve chemical problems.

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