Picture for Lu Zheng

Lu Zheng

Multi-institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume using planning-CT and FDG-PETCT

Oct 11, 2021
Figure 1 for Multi-institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume using planning-CT and FDG-PETCT
Figure 2 for Multi-institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume using planning-CT and FDG-PETCT
Figure 3 for Multi-institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume using planning-CT and FDG-PETCT
Figure 4 for Multi-institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume using planning-CT and FDG-PETCT
Viaarxiv icon

Machine learning driven synthesis of few-layered WTe2

Oct 10, 2019
Figure 1 for Machine learning driven synthesis of few-layered WTe2
Figure 2 for Machine learning driven synthesis of few-layered WTe2
Figure 3 for Machine learning driven synthesis of few-layered WTe2
Figure 4 for Machine learning driven synthesis of few-layered WTe2
Viaarxiv icon

Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization

Feb 14, 2012
Figure 1 for Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization
Figure 2 for Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization
Figure 3 for Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization
Figure 4 for Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization
Viaarxiv icon