Sang-Woon Kim

Publication Activity (10 Years)

Years Active: 1999-2022
Publications (10 Years): 16

Top Topics

Confidence Levels

Support Vector Machine

Supervised Learning Algorithms

Unlabeled Examples

Top Venues

Pattern Recognit. Lett.

Softw. Test. Verification Reliab.

Publications

Xiao-Li Wei, Chunxia Zhang, Sang-Woon Kim, Kai-Li Jing, Yong-Jun Wang, Shuang Xu, Zhuangzhuang Xie
Seismic fault detection using convolutional neural networks with focal loss. Comput. Geosci. 158 (2022)
Xiao-Li Wei, Chunxia Zhang, Hongtao Wang, Zixiang Zhao, Xiong Deng, Shuang Xu, Jiangshe Zhang, Sang-Woon Kim
Hybrid Loss-Guided Coarse-to-Fine Model for Seismic Data Consecutively Missing Trace Reconstruction. IEEE Trans. Geosci. Remote. Sens. 60 (2022)
Chun-Xia Zhang, Xiaoli Wei, Sang-Woon Kim
Empirical Evaluation on Utilizing CNN-features for Seismic Patch Classification. ICPRAM (2021)
Chun-Xia Zhang, Sang-Woon Kim, Jiang-She Zhang
On selective learning in stochastic stepwise ensembles. Int. J. Mach. Learn. Cybern. 11 (1) (2020)
Sang-Woon Kim, Joon-Min Gil
Research paper classification systems based on TF-IDF and LDA schemes. Hum. centric Comput. Inf. Sci. 9 (2019)
B. John Oommen, Sang-Woon Kim
Occlusion-based estimation of independent multinomial random variables using occurrence and sequential information. Eng. Appl. Artif. Intell. 63 (2017)
Thanh-Binh Le, Sugwon Hong, Sang-Woon Kim
Multi-view based unlabeled data selection using feature transformation methods for semiboost learning. Neurocomputing 249 (2017)
B. John Oommen, Sang-Woon Kim
On the Foundations of Multinomial Sequence Based Estimation. ICCCI (1) (2016)
Thanh-Binh Le, Sang-Woon Kim
On measuring confidence levels using multiple views of feature set for useful unlabeled data selection. Neurocomputing 173 (2016)
Yu-Seung Ma, Sang-Woon Kim
Mutation testing cost reduction by clustering overlapped mutants. J. Syst. Softw. 115 (2016)
Chun-Xia Zhang, Jiang-She Zhang, Sang-Woon Kim
PBoostGA: pseudo-boosting genetic algorithm for variable ranking and selection. Comput. Stat. 31 (4) (2016)
B. John Oommen, Sang-Woon Kim
Multinomial Sequence Based Estimation Using Contiguous Subsequences of Length Three. ICIAR (2016)
Trung Hai Nguyen, Thanh-Binh Le, Sang-Woon Kim
Choosing unlabeled examples for SemiBoost using modified cuckoo search algorithms. ICNC-FSKD (2016)
Thanh-Binh Le, Sang-Woon Kim
On Selecting Useful Unlabeled Data Using Multi-view Learning Techniques. ICPRAM (1) (2015)
Thanh-Binh Le, Sang-Woon Kim
Modified criterion to select useful unlabeled data for improving semi-supervised support vector machines. Pattern Recognit. Lett. (2015)
Thanh-Binh Le, Sang-Woon Kim
Comparison of Adjusted Methods for Selecting Useful Unlabeled Data for Semi-Supervised Learning Algorithms. IEA/AIE (2015)
Thanh-Binh Le, Sang-Woon Kim
Simply recycled selection and incrementally reinforced selection methods applicable for semi-supervised learning algorithms. ICEIC (2014)
Robert P. W. Duin, Manuele Bicego, Mauricio Orozco-Alzate, Sang-Woon Kim, Marco Loog
Metric Learning in Dissimilarity Space for Improved Nearest Neighbor Performance. S+SSPR (2014)
Thanh-Binh Le, Sang-Woon Kim
On incrementally using a small portion of strong unlabeled data for semi-supervised learning algorithms. Pattern Recognit. Lett. 41 (2014)
Thanh-Binh Le, Sang-Woon Kim
On Selecting Helpful Unlabeled Data for Improving Semi-Supervised Support Vector Machines. ICPRAM (2014)
Sang-Woon Kim
An empirical study on improving dissimilarity-based classifications using one-shot similarity measure. Digit. Signal Process. 27 (2014)
Sang-Woon Kim, Yu-Seung Ma, Yong Rae Kwon
Combining weak and strong mutation for a noninterpretive Java mutation system. Softw. Test. Verification Reliab. 23 (8) (2013)
Sang-Woon Kim
On using Additional Unlabeled Data for Improving Dissimilarity-Based Classifications. ICPRAM (2013)
Thanh-Binh Le, Sang-Woon Kim
On Improving Semi-supervised Marginboost Incrementally using Strong Unlabeled Data. ICPRAM (1) (2012)
Sang-Woon Kim, B. John Oommen
On using prototype reduction schemes to optimize locally linear reconstruction methods. Pattern Recognit. 45 (1) (2012)
Evensen E. Masaki, Sang-Woon Kim
An Improvement of Dissimilarity-Based Classifications Using SIFT Algorithm. PReMI (2011)
Sang-Woon Kim, Robert P. W. Duin
Dissimilarity-Based Classifications in Eigenspaces. CIARP (2011)
Sang-Woon Kim
An empirical evaluation on dimensionality reduction schemes for dissimilarity-based classifications. Pattern Recognit. Lett. 32 (6) (2011)
Sang-Woon Kim, Seunghwan Kim
A Multiple Combining Method for Optimizing Dissimilarity-Based Classification. ACIIDS (2) (2010)
Sang-Woon Kim
A pre-clustering technique for optimizing subclass discriminant analysis. Pattern Recognit. Lett. 31 (6) (2010)
Sang-Woon Kim
On Reducing Dimensionality of Dissimilarity Matrices for Optimizing DBC - An Experimental Comparison. ICAART (1) (2010)
Sang-Woon Kim, B. John Oommen
Linear Nearest Neighbour Reconstructions Using Prototype Reduction Schemes. Australasian Conference on Artificial Intelligence (2010)
Sang-Woon Kim, Robert P. W. Duin
An Empirical Comparison of Kernel-Based and Dissimilarity-Based Feature Spaces. SSPR/SPR (2010)
Sang-Woon Kim, Robert P. W. Duin
On Improving Dissimilarity-Based Classifications Using a Statistical Similarity Measure. CIARP (2010)
Sang-Woon Kim, B. John Oommen
On using prototype reduction schemes to enhance the computation of volume-based inter-class overlap measures. Pattern Recognit. 42 (11) (2009)
Sang-Woon Kim, Robert P. W. Duin
A Combine-Correct-Combine Scheme for Optimizing Dissimilarity-Based Classifiers. CIARP (2009)
Sang-Woon Kim, Jian Gao
On Using Dimensionality Reduction Schemes to Optimize Dissimilarity-Based Classifiers. CIARP (2008)
Sang-Woon Kim
On Optimizing Subclass Discriminant Analysis Using a Pre-clustering Technique. CIARP (2008)
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 Trans. Syst. Man Cybern. Part B 38 (2) (2008)
Sang-Woon Kim, B. John Oommen
On Using Prototype Reduction Schemes to Optimize Kernel-Based Fisher Discriminant Analysis. IEEE Trans. Syst. Man Cybern. Part B 38 (2) (2008)
Sang-Woon Kim, B. John Oommen
A Fast Computation of Inter-class Overlap Measures Using Prototype Reduction Schemes. Canadian Conference on AI (2008)
Sang-Woon Kim, Jian Gao
A Dynamic Programming Technique for Optimizing Dissimilarity-Based Classifiers. SSPR/SPR (2008)
B. John Oommen, Sang-Woon Kim, Geir Horn
On the estimation of independent binomial random variables using occurrence and sequential information. Pattern Recognit. 40 (11) (2007)
Sang-Woon Kim, B. John Oommen
On using prototype reduction schemes to optimize dissimilarity-based classification. Pattern Recognit. 40 (11) (2007)
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)
B. John Oommen, Sang-Woon Kim, Mathew Samuel, Ole-Christoffer Granmo
Stochastic Point Location in Non-stationary Environments and Its Applications. IEA/AIE (2007)
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)
Sang-Woon Kim, B. John Oommen
On Optimizing Kernel-Based Fisher Discriminant Analysis Using Prototype Reduction Schemes. SSPR/SPR (2006)
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)
Sang-Woon Kim, B. John Oommen
Prototype reduction schemes applicable for non-stationary data sets. Pattern Recognit. 39 (2) (2006)
Sang-Woon Kim
Optimizing Dissimilarity-Based Classifiers Using a Newly Modified Hausdorff Distance. PKAW (2006)
Sang-Woon Kim
On Using a Dissimilarity Representation Method to Solve the Small Sample Size Problem for Face Recognition. ACIVS (2006)
Sang-Woon Kim, Soo-Hwan Oh
On Adaptively Learning HMM-Based Classifiers Using Split-Merge Operations. IEA/AIE (2006)
Sang-Woon Kim, B. John Oommen
On Optimizing Dissimilarity-Based Classification Using Prototype Reduction Schemes. ICIAR (1) (2006)
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) (2005)
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) (2005)
Sang-Woon Kim, B. John Oommen
Time-Varying Prototype Reduction Schemes Applicable for Non-stationary Data Sets. Australian Conference on Artificial Intelligence (2005)
Sang-Woon Kim, B. John Oommen
Enhancing prototype reduction schemes with recursion: a method applicable for "large" data sets. IEEE Trans. Syst. Man Cybern. Part B 34 (3) (2004)
Sang-Woon Kim, Zhe-Xue Li, Yoshinao Aoki
On intelligent avatar communication using Korean, Chinese and Japanese sign-languages: an overview. ICARCV (2004)
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)
Sang-Woon Kim, B. John Oommen
On using prototype reduction schemes to optimize kernel-based nonlinear subspace methods. Pattern Recognit. 37 (2) (2004)
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)
Sang-Woon Kim, B. John Oommen
A brief taxonomy and ranking of creative prototype reduction schemes. Pattern Anal. Appl. 6 (3) (2003)
Sang-Woon Kim, B. John Oommen
Enhancing prototype reduction schemes with LVQ3-type algorithms. Pattern Recognit. 36 (5) (2003)
Sang-Woon Kim, B. John Oommen
On Utilizing LVQ3-Type Algorithms to Enhance Prototype Reduction Schemes. PRIS (2002)
Sang-Woon Kim, B. John Oommen
Creative prototype reduction schemes: a taxonomy and ranking. SMC (2) (2002)
Sang-Woon Kim, B. John Oommen
Recursive Prototype Reduction Schemes Applicable for Large Data Sets. SSPR/SPR (2002)
Sang-Woon Kim, B. John Oommen
Optimizing Kernel-Based Nonlinear Subspace Methods Using Prototype Reduction Schemes. Australian Joint Conference on Artificial Intelligence (2002)
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)