On the use of deep learning for phase recovery
Phase recovery (PR) refers to calculating the phase of the light field from its intensity
measurements. As exemplified from quantitative phase imaging and coherent diffraction …
measurements. As exemplified from quantitative phase imaging and coherent diffraction …
Machine learning in electron microscopy for advanced nanocharacterization: current developments, available tools and future outlook
In the last few years, electron microscopy has experienced a new methodological paradigm
aimed to fix the bottlenecks and overcome the challenges of its analytical workflow. Machine …
aimed to fix the bottlenecks and overcome the challenges of its analytical workflow. Machine …
[HTML][HTML] Self-supervised learning of hologram reconstruction using physics consistency
Existing applications of deep learning in computational imaging and microscopy mostly
depend on supervised learning, requiring large-scale, diverse and labelled training data …
depend on supervised learning, requiring large-scale, diverse and labelled training data …
Machine learning for automated experimentation in scanning transmission electron microscopy
Abstract Machine learning (ML) has become critical for post-acquisition data analysis in
(scanning) transmission electron microscopy,(S) TEM, imaging and spectroscopy. An …
(scanning) transmission electron microscopy,(S) TEM, imaging and spectroscopy. An …
AI-NERD: Elucidation of relaxation dynamics beyond equilibrium through AI-informed X-ray photon correlation spectroscopy
Understanding and interpreting dynamics of functional materials in situ is a grand challenge
in physics and materials science due to the difficulty of experimentally probing materials at …
in physics and materials science due to the difficulty of experimentally probing materials at …
Untrained deep network powered with explicit denoiser for phase recovery in inline holography
Single-shot reconstruction of the inline hologram is highly desirable as a cost-effective and
portable imaging modality in resource-constrained environments. However, the twin image …
portable imaging modality in resource-constrained environments. However, the twin image …
Deep learning at the edge enables real-time streaming ptychographic imaging
Coherent imaging techniques provide an unparalleled multi-scale view of materials across
scientific and technological fields, from structural materials to quantum devices, from …
scientific and technological fields, from structural materials to quantum devices, from …
Demonstration of an AI-driven workflow for autonomous high-resolution scanning microscopy
Modern scanning microscopes can image materials with up to sub-atomic spatial and sub-
picosecond time resolutions, but these capabilities come with large volumes of data, which …
picosecond time resolutions, but these capabilities come with large volumes of data, which …
Atomic resolution coherent x-ray imaging with physics-based phase retrieval
Coherent x-ray imaging and scattering from accelerator based sources such as synchrotrons
continue to impact biology, medicine, technology, and materials science. Many synchrotrons …
continue to impact biology, medicine, technology, and materials science. Many synchrotrons …
Practical phase retrieval using double deep image priors
Phase retrieval (PR) concerns the recovery of complex phases from complex magnitudes.
We identify the connection between the difficulty level and the number and variety of …
We identify the connection between the difficulty level and the number and variety of …