A Comparative Study on the Sign-Language Communication Systems Between Korea and Japan Through 2D and 3D Character Models on the Internet. - Sang-Woon Kim; Jong-Woo Lee; Ji-Yong Oh; Yoshinao Aoki (ICIP (4), 1999)

Optimizing Kernel-Based Nonlinear Subspace Methods Using Prototype Reduction Schemes. - Sang-Woon Kim; B. John Oommen (Australian Joint Conference on Artificial Intelligence, 2002)

On Utilizing LVQ3-Type Algorithms to Enhance Prototype Reduction Schemes. - Sang-Woon Kim; B. John Oommen (PRIS, 2002)

Creative prototype reduction schemes: a taxonomy and ranking. - Sang-Woon Kim; B. John Oommen (SMC (2), 2002)

Recursive Prototype Reduction Schemes Applicable for Large Data Sets. - Sang-Woon Kim; B. John Oommen (SSPR/SPR, 2002)

A brief taxonomy and ranking of creative prototype reduction schemes. - Sang-Woon Kim; B. John Oommen (Pattern Anal. Appl., 2003)

Enhancing prototype reduction schemes with LVQ3-type algorithms. - Sang-Woon Kim; B. John Oommen (Pattern Recognit., 2003)

Selecting Subspace Dimensions for Kernel-Based Nonlinear Subspace Classifiers Using Intelligent Search Methods. - Sang-Woon Kim; B. John Oommen (Australian Conference on Artificial Intelligence, 2004)

On intelligent avatar communication using Korean, Chinese and Japanese sign-languages: an overview. - Sang-Woon Kim; Zhe-Xue Li; Yoshinao Aoki (ICARCV, 2004)

On using prototype reduction schemes to optimize kernel-based nonlinear subspace methods. - Sang-Woon Kim; B. John Oommen (Pattern Recognit., 2004)

Enhancing prototype reduction schemes with recursion: a method applicable for "large" data sets. - Sang-Woon Kim; B. John Oommen (IEEE Trans. Syst. Man Cybern. Part B, 2004)

Time-Varying Prototype Reduction Schemes Applicable for Non-stationary Data Sets. - Sang-Woon Kim; B. John Oommen (Australian Conference on Artificial Intelligence, 2005)

On Utilizing Search Methods to Select Subspace Dimensions for Kernel-Based Nonlinear Subspace Classifiers. - Sang-Woon Kim; B. John Oommen (IEEE Trans. Pattern Anal. Mach. Intell., 2005)

On Using Prototype Reduction Schemes and Classifier Fusion Strategies to Optimize Kernel-Based Nonlinear Subspace Methods. - Sang-Woon Kim; B. John Oommen (IEEE Trans. Pattern Anal. Mach. Intell., 2005)

On Using a Dissimilarity Representation Method to Solve the Small Sample Size Problem for Face Recognition. - Sang-Woon Kim (ACIVS, 2006)

On Optimizing Dissimilarity-Based Classification Using Prototype Reduction Schemes. - Sang-Woon Kim; B. John Oommen (ICIAR (1), 2006)

On Adaptively Learning HMM-Based Classifiers Using Split-Merge Operations. - Sang-Woon Kim; Soo-Hwan Oh (IEA/AIE, 2006)

Optimizing Dissimilarity-Based Classifiers Using a Newly Modified Hausdorff Distance. - Sang-Woon Kim (PKAW, 2006)

On Optimizing Kernel-Based Fisher Discriminant Analysis Using Prototype Reduction Schemes. - Sang-Woon Kim; B. John Oommen (SSPR/SPR, 2006)

On the Theory and Applications of Sequence Based Estimation of Independent Binomial Random Variables. - B. John Oommen; Sang-Woon Kim; Geir Horn (SSPR/SPR, 2006)

Prototype reduction schemes applicable for non-stationary data sets. - Sang-Woon Kim; B. John Oommen (Pattern Recognit., 2006)

On Combining Dissimilarity-Based Classifiers to Solve the Small Sample Size Problem for Appearance-Based Face Recognition. - Sang-Woon Kim; Robert P. W. Duin (Canadian AI, 2007)

On Using a Pre-clustering Technique to Optimize LDA-Based Classifiers for Appearance-Based Face Recognition. - Sang-Woon Kim; Robert P. W. Duin (CIARP, 2007)

Stochastic Point Location in Non-stationary Environments and Its Applications. - B. John Oommen; Sang-Woon Kim; Mathew Samuel; Ole-Christoffer Granmo (IEA/AIE, 2007)

On using prototype reduction schemes to optimize dissimilarity-based classification. - Sang-Woon Kim; B. John Oommen (Pattern Recognit., 2007)

On the estimation of independent binomial random variables using occurrence and sequential information. - B. John Oommen; Sang-Woon Kim; Geir Horn (Pattern Recognit., 2007)

A Fast Computation of Inter-class Overlap Measures Using Prototype Reduction Schemes. - Sang-Woon Kim; B. John Oommen (Canadian AI, 2008)

On Optimizing Subclass Discriminant Analysis Using a Pre-clustering Technique. - Sang-Woon Kim (CIARP, 2008)

On Using Dimensionality Reduction Schemes to Optimize Dissimilarity-Based Classifiers. - Sang-Woon Kim; Jian Gao (CIARP, 2008)

A Dynamic Programming Technique for Optimizing Dissimilarity-Based Classifiers. - Sang-Woon Kim; Jian Gao (SSPR/SPR, 2008)

On Using Prototype Reduction Schemes to Optimize Kernel-Based Fisher Discriminant Analysis. - Sang-Woon Kim; B. John Oommen (IEEE Trans. Syst. Man Cybern. Part B, 2008)

A Solution to the Stochastic Point Location Problem in Metalevel Nonstationary Environments. - B. John Oommen; Sang-Woon Kim; M. T. Samuel; Ole-Christoffer Granmo (IEEE Trans. Syst. Man Cybern. Part B, 2008)

A Combine-Correct-Combine Scheme for Optimizing Dissimilarity-Based Classifiers. - Sang-Woon Kim; Robert P. W. Duin (CIARP, 2009)

On using prototype reduction schemes to enhance the computation of volume-based inter-class overlap measures. - Sang-Woon Kim; B. John Oommen (Pattern Recognit., 2009)

A Multiple Combining Method for Optimizing Dissimilarity-Based Classification. - Sang-Woon Kim; Seunghwan Kim (ACIIDS (2), 2010)

On Optimizing Locally Linear Nearest Neighbour Reconstructions Using Prototype Reduction Schemes. - Sang-Woon Kim; B. John Oommen (Australasian Conference on Artificial Intelligence, 2010)

On Improving Dissimilarity-Based Classifications Using a Statistical Similarity Measure. - Sang-Woon Kim; Robert P. W. Duin (CIARP, 2010)

On Reducing Dimensionality of Dissimilarity Matrices for Optimizing DBC - An Experimental Comparison. - Sang-Woon Kim (ICAART (1), 2010)

An Empirical Comparison of Kernel-Based and Dissimilarity-Based Feature Spaces. - Sang-Woon Kim; Robert P. W. Duin (SSPR/SPR, 2010)

A pre-clustering technique for optimizing subclass discriminant analysis. - Sang-Woon Kim (Pattern Recognit. Lett., 2010)

Dissimilarity-Based Classifications in Eigenspaces. - Sang-Woon Kim; Robert P. W. Duin (CIARP, 2011)

An Improvement of Dissimilarity-Based Classifications Using SIFT Algorithm. - Evensen E. Masaki; Sang-Woon Kim (PReMI, 2011)

An empirical evaluation on dimensionality reduction schemes for dissimilarity-based classifications. - Sang-Woon Kim (Pattern Recognit. Lett., 2011)

On Improving Semi-supervised Marginboost Incrementally using Strong Unlabeled Data. - Thanh-Binh Le; Sang-Woon Kim (ICPRAM (1), 2012)

On using prototype reduction schemes to optimize locally linear reconstruction methods. - Sang-Woon Kim; B. John Oommen (Pattern Recognit., 2012)

On using Additional Unlabeled Data for Improving Dissimilarity-Based Classifications. - Sang-Woon Kim (ICPRAM, 2013)

Combining weak and strong mutation for a noninterpretive Java mutation system. - Sang-Woon Kim; Yu-Seung Ma; Yong Rae Kwon (Softw. Test. Verification Reliab., 2013)

Simply recycled selection and incrementally reinforced selection methods applicable for semi-supervised learning algorithms. - Thanh-Binh Le; Sang-Woon Kim (ICEIC, 2014)

On Selecting Helpful Unlabeled Data for Improving Semi-Supervised Support Vector Machines. - Thanh-Binh Le; Sang-Woon Kim (ICPRAM, 2014)

Metric Learning in Dissimilarity Space for Improved Nearest Neighbor Performance. - Robert P. W. Duin; Manuele Bicego; Mauricio Orozco-Alzate; Sang-Woon Kim; Marco Loog (S+SSPR, 2014)

An empirical study on improving dissimilarity-based classifications using one-shot similarity measure. - Sang-Woon Kim (Digit. Signal Process., 2014)

On incrementally using a small portion of strong unlabeled data for semi-supervised learning algorithms. - Thanh-Binh Le; Sang-Woon Kim (Pattern Recognit. Lett., 2014)

On Selecting Useful Unlabeled Data Using Multi-view Learning Techniques. - Thanh-Binh Le; Sang-Woon Kim (ICPRAM (1), 2015)

Comparison of Adjusted Methods for Selecting Useful Unlabeled Data for Semi-Supervised Learning Algorithms. - Thanh-Binh Le; Sang-Woon Kim (IEA/AIE, 2015)

Modified criterion to select useful unlabeled data for improving semi-supervised support vector machines. - Thanh-Binh Le; Sang-Woon Kim (Pattern Recognit. Lett., 2015)

On the Foundations of Multinomial Sequence Based Estimation. - B. John Oommen; Sang-Woon Kim (ICCCI (1), 2016)

Multinomial Sequence Based Estimation Using Contiguous Subsequences of Length Three. - B. John Oommen; Sang-Woon Kim (ICIAR, 2016)

Choosing unlabeled examples for SemiBoost using modified cuckoo search algorithms. - Trung Hai Nguyen; Thanh-Binh Le; Sang-Woon Kim (ICNC-FSKD, 2016)

PBoostGA: pseudo-boosting genetic algorithm for variable ranking and selection. - Chun-Xia Zhang 002; Jiang-She Zhang 001; Sang-Woon Kim (Comput. Stat., 2016)

On measuring confidence levels using multiple views of feature set for useful unlabeled data selection. - Thanh-Binh Le; Sang-Woon Kim (Neurocomputing, 2016)

Mutation testing cost reduction by clustering overlapped mutants. - Yu-Seung Ma; Sang-Woon Kim (J. Syst. Softw., 2016)

Occlusion-based estimation of independent multinomial random variables using occurrence and sequential information. - B. John Oommen; Sang-Woon Kim (Eng. Appl. Artif. Intell., 2017)

Multi-view based unlabeled data selection using feature transformation methods for semiboost learning. - Thanh-Binh Le; Sugwon Hong; Sang-Woon Kim (Neurocomputing, 2017)

Research paper classification systems based on TF-IDF and LDA schemes. - Sang-Woon Kim; Joon-Min Gil (Hum. centric Comput. Inf. Sci., 2019)

On selective learning in stochastic stepwise ensembles. - Chun-Xia Zhang 002; Sang-Woon Kim; Jiang-She Zhang 001 (Int. J. Mach. Learn. Cybern., 2020)

Empirical Evaluation on Utilizing CNN-features for Seismic Patch Classification. - Chun-Xia Zhang 002; Xiaoli Wei; Sang-Woon Kim (ICPRAM, 2021)

Seismic fault detection using convolutional neural networks with focal loss. - Xiao-Li Wei; Chunxia Zhang 002; Sang-Woon Kim; Kai-Li Jing; Yong-Jun Wang; Shuang Xu; Zhuangzhuang Xie (Comput. Geosci., 2022)

Hybrid Loss-Guided Coarse-to-Fine Model for Seismic Data Consecutively Missing Trace Reconstruction. - Xiao-Li Wei; Chunxia Zhang 002; Hongtao Wang; Zixiang Zhao; Xiong Deng; Shuang Xu; Jiangshe Zhang 001; Sang-Woon Kim (IEEE Trans. Geosci. Remote. Sens., 2022)

Seismic Data Interpolation via Denoising Diffusion Implicit Models With Coherence-Corrected Resampling. - Xiao-Li Wei; Chunxia Zhang 002; Hongtao Wang; Chengli Tan; Deng Xiong; Baisong Jiang; Jiangshe Zhang 001; Sang-Woon Kim (IEEE Trans. Geosci. Remote. Sens., 2024)