Sparse sampling of reflectance with five strategically chosen near-IR bandpass filters combined with a multivariate Gaussian model enables non-destructive thickness mapping of 3R-MoS2 on PDMS up to 691 nm with average 8.3 nm 95% CI width.
Recent advances in techniques for hyperspectral image processing
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SpectralTrain is a universal training framework that combines curriculum learning and PCA spectral downsampling to deliver 2-7x faster training for hyperspectral image classification across multiple backbones and datasets with only small accuracy trade-offs.
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Sparse Spectral Imaging for Thickness Mapping of 3R-MoS$_2$ on PDMS
Sparse sampling of reflectance with five strategically chosen near-IR bandpass filters combined with a multivariate Gaussian model enables non-destructive thickness mapping of 3R-MoS2 on PDMS up to 691 nm with average 8.3 nm 95% CI width.
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SpectralTrain: A Universal Framework for Hyperspectral Image Classification
SpectralTrain is a universal training framework that combines curriculum learning and PCA spectral downsampling to deliver 2-7x faster training for hyperspectral image classification across multiple backbones and datasets with only small accuracy trade-offs.