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spectrai: A deep learning framework for spectral data

arXiv 2108.07595 ↗First posted 17 Aug 2021eess.IV cs.CVcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 20 of its 54 references that are in the map. First posted on arXiv 17 Aug 2021.

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References · 20

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8 more
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