1 citations · 1 across the 2 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2024★ 1 cited
A versatile machine learning workflow for high-throughput analysis of supported metal catalyst particles
Arda Genc, Justin Marlowe, Anika Jalil +2
Accurate and efficient characterization of nanoparticles (NPs), particularly regarding particle size distribution, is essential for advancing our understanding of their structure-p…
cond-mat.mtrl-sci2022
A Deep Learning Approach for Semantic Segmentation of Unbalanced Data in Electron Tomography of Catalytic Materials
Arda Genc, Libor Kovarik, Hamish L. Fraser
Heterogeneous catalysts possess complex surface and bulk structures, relatively poor intrinsic contrast, and often a sparse distribution of the catalytic nanoparticles (NPs), posin…