A two-branch deep neural network using lateral and longitudinal diffraction features achieves high extraction rates and speeds for holographic 3D particle imaging, with broad generalizability claimed but only partially validated.
Holographic characterization of protein aggregates,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.optics 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy
A two-branch deep neural network using lateral and longitudinal diffraction features achieves high extraction rates and speeds for holographic 3D particle imaging, with broad generalizability claimed but only partially validated.