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Search Publications by: Jin Chu Wu (Assoc)

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Displaying 1 - 25 of 64

Monte Carlo studies of bootstrap variability in ROC analysis with data dependency

August 1, 2019
Author(s)
Jin Chu Wu, Alvin F. Martin, Raghu N. Kacker
ROC analysis involving two large datasets is an important method for analyzing statistics of interest for decision making of a classifier in many disciplines. And data dependency due to multiple use of the same subjects exists ubiquitously in order to

A novel measure and significance testing in data analysis of cell image segmentation

April 20, 2017
Author(s)
Jin Chu Wu, Michael W. Halter, Raghu N. Kacker, John T. Elliott, Anne L. Plant
Background: Cell image segmentation (CIS) is an essential part of quantitative imaging of biological cells. Designing a performance measure and conducting significance testing are critical for evaluating and comparing the CIS algorithms for image-based

The Impact of Data Dependency on Speaker Recognition Evaluation

February 8, 2017
Author(s)
Jin Chu Wu, Alvin F. Martin, Craig S. Greenberg, Raghu N. Kacker
The data dependency due to multiple use of the same subjects has impact on the standard error (SE) of the detection cost function (DCF) in speaker recognition evaluation. The DCF is defined as a weighted sum of the probabilities of type I and type II

Bootstrap Variability Studies in ROC Analysis on Large Datasets

March 19, 2014
Author(s)
Jin Chu Wu, Alvin F. Martin, Raghu N. Kacker
The nonparametric two-sample bootstrap is employed to compute uncertainties of measures in receiver operating characteristic (ROC) analysis on large datasets in areas such as biometrics, and so on. In this framework, the bootstrap variability was

Measurement Uncertainty in Cell Image Segmentation Data Analysis

August 13, 2013
Author(s)
Jin Chu Wu, Michael W. Halter, Raghu N. Kacker, John T. Elliott, Anne L. Plant
Cell image segmentation is a part of quantitative studies regarding cell movement and cell behavior, and it plays a critical role in molecular biology and cellular biochemistry. Therefore, it is fundamentally important to evaluate the performance levels of

Significance Test with Data Dependency in Speaker Recognition Evaluation

July 25, 2013
Author(s)
Jin Chu Wu, Alvin F. Martin, Craig S. Greenberg, Raghu N. Kacker, Vincent M. Stanford
To evaluate the performance of speaker recognition systems, a detection cost function defined as a weighted sum of the probabilities of type I and type II errors is employed. The speaker datasets may have data dependency due to multiple uses of the same

Significance Test in Speaker Recognition Data Analysis with Data Dependency

October 17, 2012
Author(s)
Jin Chu Wu, Alvin F. Martin, Craig S. Greenberg, Raghu N. Kacker, Vincent M. Stanford
To evaluate the performance of speaker recognition systems, a detection cost function defined as a weighted sum of the probabilities of type I and type II errors is employed. The speaker datasets may have data dependency due to multiple uses of the same

An Exploration of the Operational Ramifications of Lossless Compression of 1000 ppi Fingerprint Imagery

August 6, 2012
Author(s)
Shahram Orandi, John M. Libert, John D. Grantham, Kenneth Ko, Stephen S. Wood, Jin Chu Wu, Lindsay M. Petersen, Bruce Bandini
This paper presents the findings of a study initially conducted to measure the operational impact of JPEG 2000 lossy compression on 1000 ppi fingerprint imagery at various levels of compression, but later expanded to include lossless compression. Lossless