| 2008 |
| 13 | | Zhaojia Sun,
Miseon Choi,
Cheong Hee Park,
Young-Kuk Kim:
Selection Of Orthogonal Features In Fisher Discriminant Analysis.
IADIS European Conf. Data Mining 2008: 102-106 |
| 12 | EE | Moonhwi Lee,
Cheong Hee Park:
An efficient image normalization method for face recognition under varying illuminations.
Multimedia Information Retrieval 2008: 128-133 |
| 11 | EE | Cheong Hee Park,
Haesun Park:
A comparison of generalized linear discriminant analysis algorithms.
Pattern Recognition 41(3): 1083-1097 (2008) |
| 10 | EE | Cheong Hee Park,
Moonhwi Lee:
On applying linear discriminant analysis for multi-labeled problems.
Pattern Recognition Letters 29(7): 878-887 (2008) |
| 2007 |
| 9 | EE | Cheong Hee Park,
Hongsuk Shim:
On Detecting an Emerging Class.
GrC 2007: 265-270 |
| 8 | EE | Moonhwi Lee,
Cheong Hee Park:
On Applying Dimension Reduction for Multi-labeled Problems.
MLDM 2007: 131-143 |
| 2006 |
| 7 | EE | Cheong Hee Park:
Similarity-Based Sparse Feature Extraction Using Local Manifold Learning.
PAKDD 2006: 30-34 |
| 2005 |
| 6 | EE | Cheong Hee Park,
Haesun Park:
Fingerprint classification using fast Fourier transform and nonlinear discriminant analysis.
Pattern Recognition 38(4): 495-503 (2005) |
| 2004 |
| 5 | EE | Cheong Hee Park,
Haesun Park,
Panos M. Pardalos:
A Comparative Study of Linear and Nonlinear Feature Extraction Methods.
ICDM 2004: 495-498 |
| 4 | EE | Jieping Ye,
Ravi Janardan,
Cheong Hee Park,
Haesun Park:
An Optimization Criterion for Generalized Discriminant Analysis on Undersampled Problems.
IEEE Trans. Pattern Anal. Mach. Intell. 26(8): 982-994 (2004) |
| 3 | EE | Cheong Hee Park,
Haesun Park:
Nonlinear feature extraction based on centroids and kernel functions.
Pattern Recognition 37(4): 801-810 (2004) |
| 2003 |
| 2 | EE | Cheong Hee Park,
Haesun Park:
Efficient Nonlinear Dimension Reduction for Clustered Data Using Kernel Functions.
ICDM 2003: 243-250 |
| 1 | EE | Jieping Ye,
Ravi Janardan,
Cheong Hee Park,
Haesun Park:
A new optimization criterion for generalized discriminant analysis on undersampled problems.
ICDM 2003: 419-426 |