spectrai: A deep learning framework for spectral data

• URL: http://arxiv.org/abs/2108.07595v1
• Date: Tue, 17 Aug 2021 12:54:34 GMT
• Title: spectrai: A deep learning framework for spectral data
• Authors: Conor C. Horgan and Mads S. Bergholt
• Abstract summary: We present spectrai, an open-source framework designed to facilitate the training of neural networks on spectral data. Specti provides numerous built-in spectral data pre-processing and augmentation methods, neural networks for spectral data including spectral (image) denoising, spectral (image) classification, spectral image segmentation, and spectral image super-resolution.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Deep learning computer vision techniques have achieved many successes in recent years across numerous imaging domains. However, the application of deep learning to spectral data remains a complex task due to the need for augmentation routines, specific architectures for spectral data, and significant memory requirements. Here we present spectrai, an open-source deep learning framework designed to facilitate the training of neural networks on spectral data and enable comparison between different methods. Spectrai provides numerous built-in spectral data pre-processing and augmentation methods, neural networks for spectral data including spectral (image) denoising, spectral (image) classification, spectral image segmentation, and spectral image super-resolution. Spectrai includes both command line and graphical user interfaces (GUI) designed to guide users through model and hyperparameter decisions for a wide range of applications.

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