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Multi-mode fiber reservoir computing overcomes shallow neural networks classifiers
In the field of disordered photonics, a common objective is to characterize optically opaque materials for controlling light delivery or performing imaging.
Beyond multi-view deconvolution for inherently-aligned fluorescence tomography
In multi-view fluorescence microscopy, each angular acquisition needs to be aligned with care to obtain an optimal volumetric reconstruction.
Transmission Matrix Inference via Pseudolikelihood Decimation
One of the biggest challenges in the field of biomedical imaging is the comprehension and the exploitation of the photon scattering through disordered media.
Learning Direct and Inverse Transmission Matrices
Linear problems appear in a variety of disciplines and their application for the transmission matrix recovery is one of the most stimulating challenges in biomedical imaging.
