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A Deep Learning Approach for Semantic Segmentation of Unbalanced Data in
  Electron Tomography of Catalytic Materials

A Deep Learning Approach for Semantic Segmentation of Unbalanced Data in Electron Tomography of Catalytic Materials

18 January 2022
A. Genç
L. Kovarik
H. Fraser
ArXivPDFHTML

Papers citing "A Deep Learning Approach for Semantic Segmentation of Unbalanced Data in Electron Tomography of Catalytic Materials"

2 / 2 papers shown
Title
A versatile machine learning workflow for high-throughput analysis of
  supported metal catalyst particles
A versatile machine learning workflow for high-throughput analysis of supported metal catalyst particles
A. Genç
Justin Marlowe
Anika Jalil
L. Kovarik
Phillip Christopher
32
1
0
02 Oct 2024
Unified Focal loss: Generalising Dice and cross entropy-based losses to
  handle class imbalanced medical image segmentation
Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation
Michael Yeung
Evis Sala
Carola-Bibiane Schönlieb
L. Rundo
30
393
0
08 Feb 2021
1