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Author

Carlo Manzo

2 papers indexed here

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Oct 2026

ASAP (AFM simulation and analysis pipeline): a unified deep learning framework for simulation, quality control, and segmentation in atomic force microscopy

Atomic force microscopy (AFM) provides nanoscale images and force–distance curves (FDCs), but increasingly large datasets make manual analysis a major bottleneck. Deep learning can automate feature extraction, quality control, and segmentation, yet its use in AFM is often limited by scarce ground-truth data and the tec...

Prakhar Dutta, Jia-Cheng Huang, Nazli Demirpehlivan et al. · 0 citations
#graph neural networks Review Oct 2026

Particle tracking in quantitative microscopy: a modular tutorial on classical and deep learning methods

Particle tracking is a central tool in digital microscopy for quantifying micro- and nanoscale dynamics. Selecting and validating appropriate methods remains challenging, particularly under low signal-to-noise ratios or high particle densities and for researchers with limited computational expertise. In this talk, we p...

Aaron Domenzain Del Castillo Cerecer, Alex Lech, Jesco Schönfelder et al. · 0 citations

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