1 citations · 3 across the 4 of their papers we have counts for
4 papers
Atomic Depth Estimation From Noisy Electron Microscopy Data Via Deep Learning
Matan Leibovich, Mai Tan, Ramon Manzorro +4
We present a novel approach for extracting 3D atomic-level information from transmission electron microscopy (TEM) images affected by significant noise. The approach is based on fo…
Revealing Information from Weak Signal in Electron Energy-Loss Spectroscopy with a Deep Denoiser
Yifan Wang, Mai Tan, Carlos Fernandez-Granda +1
Electron energy-loss spectroscopy (EELS) coupled with scanning transmission electron microscopy (STEM) is a powerful technique to determine materials composition and bonding with h…
Atomic Resolution Observations of Nanoparticle Surface Dynamics and Instabilities Enabled by Artificial Intelligence
Peter A. Crozier, Matan Leibovich, Piyush Haluai +9
Nanoparticle surface structural dynamics is believed to play a significant role in regulating functionalities such as diffusion, reactivity, and catalysis but the atomic-level proc…
Evaluating Unsupervised Denoising Requires Unsupervised Metrics
Adria Marcos-Morales, Matan Leibovich, Sreyas Mohan +5
Unsupervised denoising is a crucial challenge in real-world imaging applications. Unsupervised deep-learning methods have demonstrated impressive performance on benchmarks based on…