Trained correlated-photon illumination paired with a Transformer backend improves object classification accuracy by up to 15 percentage points in photon-starved noisy imaging.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Orthogonalised SGQT adapts orthogonalisation from single-pixel imaging to improve quantum tomography fidelity from 95.2% to 99.17% numerically and 92.1% to 95.3% experimentally.
citing papers explorer
-
Ultra-low-light computer vision using trained photon correlations
Trained correlated-photon illumination paired with a Transformer backend improves object classification accuracy by up to 15 percentage points in photon-starved noisy imaging.
-
Orthogonalised Self-Guided Quantum Tomography: Insights from Single-Pixel Imaging
Orthogonalised SGQT adapts orthogonalisation from single-pixel imaging to improve quantum tomography fidelity from 95.2% to 99.17% numerically and 92.1% to 95.3% experimentally.