 | 2009 |
|---|
| 34 |       | Sang-Woon Kim,
Robert P. W. Duin:
A Combine-Correct-Combine Scheme for Optimizing Dissimilarity-Based Classifiers.
CIARP 2009: 425-432 |
| 33 | | Sang-Woon Kim,
B. John Oommen:
On using prototype reduction schemes to enhance the computation of volume-based inter-class overlap measures.
Pattern Recognition 42(11): 2695-2704 (2009) |
| 2008 |
|---|
| 32 | | Sang-Woon Kim:
On Optimizing Subclass Discriminant Analysis Using a Pre-clustering Technique.
CIARP 2008: 292-300 |
| 31 | | Sang-Woon Kim,
Jian Gao:
On Using Dimensionality Reduction Schemes to Optimize Dissimilarity-Based Classifiers.
CIARP 2008: 309-316 |
| 30 | | Sang-Woon Kim,
B. John Oommen:
A Fast Computation of Inter-class Overlap Measures Using Prototype Reduction Schemes.
Canadian Conference on AI 2008: 173-184 |
| 29 | | Sang-Woon Kim,
Jian Gao:
A Dynamic Programming Technique for Optimizing Dissimilarity-Based Classifiers.
SSPR/SPR 2008: 654-663 |
| 28 | | B. John Oommen,
Sang-Woon Kim,
M. T. Samuel,
Ole-Christoffer Granmo:
A Solution to the Stochastic Point Location Problem in Metalevel Nonstationary Environments.
IEEE Transactions on Systems, Man, and Cybernetics, Part B 38(2): 466-476 (2008) |
| 27 | | Sang-Woon Kim,
B. John Oommen:
On Using Prototype Reduction Schemes to Optimize Kernel-Based Fisher Discriminant Analysis.
IEEE Transactions on Systems, Man, and Cybernetics, Part B 38(2): 564-570 (2008) |
| 2007 |
|---|
| 26 | | Sang-Woon Kim,
Robert P. W. Duin:
On Using a Pre-clustering Technique to Optimize LDA-Based Classifiers for Appearance-Based Face Recognition.
CIARP 2007: 466-476 |
| 25 | | Sang-Woon Kim,
Robert P. W. Duin:
On Combining Dissimilarity-Based Classifiers to Solve the Small Sample Size Problem for Appearance-Based Face Recognition.
Canadian Conference on AI 2007: 110-121 |
| 24 | | B. John Oommen,
Sang-Woon Kim,
Mathew Samuel,
Ole-Christoffer Granmo:
Stochastic Point Location in Non-stationary Environments and Its Applications.
IEA/AIE 2007: 845-854 |
| 23 | | Sang-Woon Kim,
B. John Oommen:
On using prototype reduction schemes to optimize dissimilarity-based classification.
Pattern Recognition 40(11): 2946-2957 (2007) |
| 22 | | B. John Oommen,
Sang-Woon Kim,
Geir Horn:
On the estimation of independent binomial random variables using occurrence and sequential information.
Pattern Recognition 40(11): 3263-3276 (2007) |
| 2006 |
|---|
| 21 | | Sang-Woon Kim:
On Using a Dissimilarity Representation Method to Solve the Small Sample Size Problem for Face Recognition.
ACIVS 2006: 1174-1185 |
| 20 | | Sang-Woon Kim,
B. John Oommen:
On Optimizing Dissimilarity-Based Classification Using Prototype Reduction Schemes.
ICIAR (1) 2006: 15-28 |
| 19 | | Sang-Woon Kim,
Soo-Hwan Oh:
On Adaptively Learning HMM-Based Classifiers Using Split-Merge Operations.
IEA/AIE 2006: 668-673 |
| 18 | | Sang-Woon Kim:
Optimizing Dissimilarity-Based Classifiers Using a Newly Modified Hausdorff Distance.
PKAW 2006: 177-186 |
| 17 | | B. John Oommen,
Sang-Woon Kim,
Geir Horn:
On the Theory and Applications of Sequence Based Estimation of Independent Binomial Random Variables.
SSPR/SPR 2006: 8-21 |
| 16 | | Sang-Woon Kim,
B. John Oommen:
On Optimizing Kernel-Based Fisher Discriminant Analysis Using Prototype Reduction Schemes.
SSPR/SPR 2006: 826-834 |
| 15 | | Sang-Woon Kim,
B. John Oommen:
Prototype reduction schemes applicable for non-stationary data sets.
Pattern Recognition 39(2): 209-222 (2006) |
| 2005 |
|---|
| 14 | | Sang-Woon Kim,
B. John Oommen:
Time-Varying Prototype Reduction Schemes Applicable for Non-stationary Data Sets.
Australian Conference on Artificial Intelligence 2005: 614-623 |
| 13 | | Sang-Woon Kim,
B. John Oommen:
On Utilizing Search Methods to Select Subspace Dimensions for Kernel-Based Nonlinear Subspace Classifiers.
IEEE Trans. Pattern Anal. Mach. Intell. 27(1): 136-141 (2005) |
| 12 | | Sang-Woon Kim,
B. John Oommen:
On Using Prototype Reduction Schemes and Classifier Fusion Strategies to Optimize Kernel-Based Nonlinear Subspace Methods.
IEEE Trans. Pattern Anal. Mach. Intell. 27(3): 455-460 (2005) |
| 2004 |
|---|
| 11 | | Sang-Woon Kim,
B. John Oommen:
Selecting Subspace Dimensions for Kernel-Based Nonlinear Subspace Classifiers Using Intelligent Search Methods.
Australian Conference on Artificial Intelligence 2004: 1115-1121 |
| 10 | | Sang-Woon Kim,
Zhe-Xue Li,
Yoshinao Aoki:
On intelligent avatar communication using Korean, Chinese and Japanese sign-languages: an overview.
ICARCV 2004: 747-752 |
| 9 | | Sang-Woon Kim,
B. John Oommen:
Enhancing prototype reduction schemes with recursion: a method applicable for "large" data sets.
IEEE Transactions on Systems, Man, and Cybernetics, Part B 34(3): 1384-1397 (2004) |
| 8 | | Sang-Woon Kim,
B. John Oommen:
On using prototype reduction schemes to optimize kernel-based nonlinear subspace methods.
Pattern Recognition 37(2): 227-239 (2004) |
| 2003 |
|---|
| 7 | | Sang-Woon Kim,
B. John Oommen:
On Using Prototype Reduction Schemes and Classifier Fusion Strategies to Optimize Kernel-Based Nonlinear Subspace Methods.
Australian Conference on Artificial Intelligence 2003: 783-795 |
| 6 | | Sang-Woon Kim,
B. John Oommen:
A brief taxonomy and ranking of creative prototype reduction schemes.
Pattern Anal. Appl. 6(3): 232-244 (2003) |
| 5 | | Sang-Woon Kim,
B. John Oommen:
Enhancing prototype reduction schemes with LVQ3-type algorithms.
Pattern Recognition 36(5): 1083-1093 (2003) |
| 2002 |
|---|
| 4 | | Sang-Woon Kim,
B. John Oommen:
Optimizing Kernel-Based Nonlinear Subspace Methods Using Prototype Reduction Schemes.
Australian Joint Conference on Artificial Intelligence 2002: 155-166 |
| 3 |  | Sang-Woon Kim,
B. John Oommen:
On Utilizing LVQ3-Type Algorithms to Enhance Prototype Reduction Schemes.
PRIS 2002: 242-256 |
| 2 | | Sang-Woon Kim,
B. John Oommen:
Recursive Prototype Reduction Schemes Applicable for Large Data Sets.
SSPR/SPR 2002: 528-537 |
| 1999 |
|---|
| 1 | | Sang-Woon Kim,
Jong-Woo Lee,
Ji-Yong Oh,
Yoshinao Aoki:
A Comparative Study on the Sign-Language Communication Systems Between Korea and Japan Through 2D and 3D Character Models on the Internet.
ICIP (4) 1999: 227-231 |
