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Te-Won Lee

Showing results (11-20 of 26) with videos related to

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IEEE Transactions on Audio, Speech, and Language Processing|April 30, 2010
Speech Enhancement, Gain, and Noise Spectrum Adaptation Using Approximate Bayesian EstimationJiucang Hao, Hagai Attias, Srikantan Nagarajan, et al.
IEEE Transactions on Bio-Medical Engineering|September 7, 2002
Comparison of machine learning and traditional classifiers in glaucoma diagnosisKwokleung Chan, Te-Won Lee, Pamela A Sample, et al.
Neural Computation|February 20, 2003
Dictionary learning algorithms for sparse representationKenneth Kreutz-Delgado, Joseph F Murray, Bhaskar D Rao, et al.
Proceedings of the IEEE. Institute of Electrical and Electronics Engineers|September 9, 2010
Imaging Brain Dynamics Using Independent Component AnalysisTzyy-Ping Jung, Scott Makeig, Martin J McKeown, et al.
Investigative Ophthalmology & Visual Science|October 31, 2002
Comparing neural networks and linear discriminant functions for glaucoma detection using confocal scanning laser ophthalmoscopy of the optic discChristopher Bowd, Kwokleung Chan, Linda M Zangwill, et al.
Transactions of the American Ophthalmological Society|April 23, 2008
Machine learning classifiers detect subtle field defects in eyes of HIV individualsIgor Kozak, Pamela A Sample, Jiucang Hao, et al.
Investigative Ophthalmology & Visual Science|August 25, 2004
Heidelberg retina tomograph measurements of the optic disc and parapapillary retina for detecting glaucoma analyzed by machine learning classifiersLinda M Zangwill, Kwokleung Chan, Christopher Bowd, et al.
Investigative Ophthalmology & Visual Science|March 26, 2005
Relevance vector machine and support vector machine classifier analysis of scanning laser polarimetry retinal nerve fiber layer measurementsChristopher Bowd, Felipe A Medeiros, Zuohua Zhang, et al.
Journal of Glaucoma|June 17, 2009
Combining functional and structural tests improves the diagnostic accuracy of relevance vector machine classifiersLyne Racette, Christine Y Chiou, Jiucang Hao, et al.
Investigative Ophthalmology & Visual Science|March 11, 2008
Bayesian machine learning classifiers for combining structural and functional measurements to classify healthy and glaucomatous eyesChristopher Bowd, Jiucang Hao, Ivan M Tavares, et al.
Pageof 3

Showing results (11-20 of 26) with videos related to

Sort By:
Pageof 3
IEEE Transactions on Audio, Speech, and Language Processing|April 30, 2010
Speech Enhancement, Gain, and Noise Spectrum Adaptation Using Approximate Bayesian EstimationJiucang Hao, Hagai Attias, Srikantan Nagarajan, et al.
IEEE Transactions on Bio-Medical Engineering|September 7, 2002
Comparison of machine learning and traditional classifiers in glaucoma diagnosisKwokleung Chan, Te-Won Lee, Pamela A Sample, et al.
Neural Computation|February 20, 2003
Dictionary learning algorithms for sparse representationKenneth Kreutz-Delgado, Joseph F Murray, Bhaskar D Rao, et al.
Proceedings of the IEEE. Institute of Electrical and Electronics Engineers|September 9, 2010
Imaging Brain Dynamics Using Independent Component AnalysisTzyy-Ping Jung, Scott Makeig, Martin J McKeown, et al.
Investigative Ophthalmology & Visual Science|October 31, 2002
Comparing neural networks and linear discriminant functions for glaucoma detection using confocal scanning laser ophthalmoscopy of the optic discChristopher Bowd, Kwokleung Chan, Linda M Zangwill, et al.
Transactions of the American Ophthalmological Society|April 23, 2008
Machine learning classifiers detect subtle field defects in eyes of HIV individualsIgor Kozak, Pamela A Sample, Jiucang Hao, et al.
Investigative Ophthalmology & Visual Science|August 25, 2004
Heidelberg retina tomograph measurements of the optic disc and parapapillary retina for detecting glaucoma analyzed by machine learning classifiersLinda M Zangwill, Kwokleung Chan, Christopher Bowd, et al.
Investigative Ophthalmology & Visual Science|March 26, 2005
Relevance vector machine and support vector machine classifier analysis of scanning laser polarimetry retinal nerve fiber layer measurementsChristopher Bowd, Felipe A Medeiros, Zuohua Zhang, et al.
Journal of Glaucoma|June 17, 2009
Combining functional and structural tests improves the diagnostic accuracy of relevance vector machine classifiersLyne Racette, Christine Y Chiou, Jiucang Hao, et al.
Investigative Ophthalmology & Visual Science|March 11, 2008
Bayesian machine learning classifiers for combining structural and functional measurements to classify healthy and glaucomatous eyesChristopher Bowd, Jiucang Hao, Ivan M Tavares, et al.
Pageof 3