7 citations · 9 across the 5 of their papers we have counts for
5 papers
Universal computational super-resolution framework for imaging of quantum dots
Dominik Vašinka, Jaewon Lee, Charlie Stalker +9
We present a universal deep-learning method that reconstructs super-resolved images of quantum emitters from a single camera frame measurement. Trained on physics-based synthetic d…
Calibration-free single-frame super-resolution fluorescence microscopy
Anežka Dostálová, Dominik Vašinka, Robert Stárek +1
Molecular fluorescence microscopy is a leading approach to super-resolution and nanoscale imaging in life and material sciences. However, super-resolution fluorescence microscopy i…
From Stars to Molecules: AI Guided Device-Agnostic Super-Resolution Imaging
Dominik Vašinka, Filip Juráň, Jaromír Běhal +1
Super-resolution imaging has revolutionized the study of systems ranging from molecular structures to distant galaxies. However, existing super-resolution methods require extensive…
All-fiber microendoscopic polarization sensing at single-photon level aided by deep-learning
Martin Bielak, Dominik Vašinka, Miroslav Ježek
The polarization of light conveys crucial information about the spatial ordering and optical properties of a specimen. However, precise polarization measurement in challenging cond…
Bidirectional deep learning of polarization transfer in liquid crystals with application to quantum state preparation
Dominik Vašinka, Martin Bielak, Michal Neset +1
Accurate control of light polarization represents a core building block in polarization metrology, imaging, and optical and quantum communications. Voltage-controlled liquid crysta…