GS-DOT represents absorption in diffuse optical tomography as a sparse sum of anisotropic Gaussians optimized with Adam to match time-resolved measurements, replacing ray transport with diffusion functions for the first time in this regime.
Adam: A method for stochastic optimization
2 Pith papers cite this work. Polarity classification is still indexing.
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A SqueezeNet CNN classifies immune cells from label-free multiphoton autofluorescence images, achieving 0.89 ROC-AUC for binary classification and 0.689 F1 for six-class tasks.
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Detecting immune cells with label-free two-photon autofluorescence and deep learning
A SqueezeNet CNN classifies immune cells from label-free multiphoton autofluorescence images, achieving 0.89 ROC-AUC for binary classification and 0.689 F1 for six-class tasks.