Ze Jin

According to our database1, Ze Jin authored at least 13 papers between 2013 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 


On csauthors.net:


Obtaining the potential number of object models/atlases needed in medical image analysis.
Proceedings of the Medical Imaging 2020: Image-Guided Procedures, 2020

Approximate Quantiles for Datacenter Telemetry Monitoring.
Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

Optimization and testing in linear non-Gaussian component analysis.
Stat. Anal. Data Min., 2019

How many models/atlases are needed as priors for capturing anatomic population variations?
Medical Image Anal., 2019

NetBouncer: Active Device and Link Failure Localization in Data Center Networks.
Proceedings of the 16th USENIX Symposium on Networked Systems Design and Implementation, 2019

Obtaining the potential number of models/atlases needed for capturing anatomic variations in population images.
Proceedings of the Medical Imaging 2019: Image Processing, 2019

Independent Component Analysis Based on Mutual Dependence Measures.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Development of Deep-learning Segmentation for Breast Cancer in MR Images based on Neural Network Convolution.
Proceedings of the ICCPR '19: 8th International Conference on Computing and Pattern Recognition, 2019

Generalizing distance covariance to measure and test multivariate mutual dependence via complete and incomplete V-statistics.
J. Multivar. Anal., 2018

Testing for Conditional Mean Independence with Covariates through Martingale Difference Divergence.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

The difference-of-datasets framework: A statistical method to discover insight.
Proceedings of the 2016 IEEE International Conference on Big Data, 2016

Initial Seeds Selection in Dynamic Clustering Method Based on Data Depth.
Proceedings of the Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques, 2015

Automated method for extraction of lung tumors using a machine learning classifier with knowledge of radiation oncologists on data sets of planning CT and FDG-PET/CT images.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013