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Found 5 papers, 2 papers with code
AI-assisted Automated Workflow for Real-time X-ray Ptychography Data Analysis via Federated Resources
We present an end-to-end automated workflow that uses large-scale remote compute resources and an embedded GPU platform at the edge to enable AI/ML-accelerated real-time analysis of data collected for x-ray ptychography.
Deep learning at the edge enables real-time streaming ptychographic imaging
Coherent microscopy techniques provide an unparalleled multi-scale view of materials across scientific and technological fields, from structural materials to quantum devices, from integrated circuits to biological cells.
A matrix-free Levenberg-Marquardt algorithm for efficient ptychographic phase retrieval
The phase retrieval problem, where one aims to recover a complex-valued image from far-field intensity measurements, is a classic problem encountered in a range of imaging applications.
Real-time 3D Nanoscale Coherent Imaging via Physics-aware Deep Learning
Phase retrieval, the problem of recovering lost phase information from measured intensity alone, is an inverse problem that is widely faced in various imaging modalities ranging from astronomy to nanoscale imaging.
Three dimensions, two microscopes, one code: automatic differentiation for x-ray nanotomography beyond the depth of focus limit
Conventional tomographic reconstruction algorithms assume that one has obtained pure projection images, involving no within-specimen diffraction effects nor multiple scattering.
Image and Video Processing Applied Physics Optics
