Hee-Seok Oh

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 26

Top Topics

Von Mises Fisher

Quantile Regression

Image Decomposition

Top Venues

Pattern Recognit. Lett.

J. Multivar. Anal.

Publications

Seungwoo Kang, Hee-Seok Oh
Probabilistic Principal Curves on Riemannian Manifolds. IEEE Trans. Pattern Anal. Mach. Intell. 46 (7) (2024)
Seungwoo Kang, Hee-Seok Oh
Novel sampling method for the von Mises-Fisher distribution. Stat. Comput. 34 (3) (2024)
Hyeonglae Cho, Hee-Seok Oh, Donghoh Kim
GSD: An R package for graph signal decomposition. SoftwareX 26 (2024)
Guebin Choi, Hee-Seok Oh
Decomposition via elastic-band transform. Pattern Recognit. Lett. 182 (2024)
Yeonjoo Park, Hee-Seok Oh, Yaeji Lim
A data-adaptive dimension reduction for functional data via penalized low-rank approximation. Stat. Comput. 34 (1) (2024)
Joonpyo Kim, Hee-Seok Oh, Haeran Cho
Moving Sum Procedure for Change Point Detection under Piecewise Linearity. Technometrics 66 (3) (2024)
Minji Kim, Hee-Seok Oh, Yaeji Lim
Zero-Inflated Time Series Clustering Via Ensemble Thick-Pen Transform. J. Classif. 40 (2) (2023)
Guebin Choi, Hee-Seok Oh
Elastic-band transform for visualization and detection. Pattern Recognit. Lett. 166 (2023)
Jongmin Lee, Hee-Seok Oh
Robust spherical principal curves. Pattern Recognit. 138 (2023)
Ha Young Shin, Hee-Seok Oh
Robust Geodesic Regression. Int. J. Comput. Vis. 130 (2) (2022)
Hee-Seok Oh, Guebin Choi, Donghoh Kim
Decomp2d: An R solution for image decomposition. SoftwareX 19 (2022)
Jongmin Lee, Jang-Hyun Kim, Hee-Seok Oh
spherepc: An R Package for Dimension Reduction on a Sphere. R J. 14 (1) (2022)
Donghoh Kim, Hee-Seok Oh, Guebin Choi
EPT: An R package for ensemble patch transform. SoftwareX 14 (2021)
Jongmin Lee, Jang-Hyun Kim, Hee-Seok Oh
Spherical Principal Curves. IEEE Trans. Pattern Anal. Mach. Intell. 43 (6) (2021)
Yaeji Lim, Junhyeon Kwon, Hee-Seok Oh
Principal component analysis in the wavelet domain. Pattern Recognit. 119 (2021)
Donghoh Kim, Guebin Choi, Hee-Seok Oh
Ensemble patch transformation: a flexible framework for decomposition and filtering of signal. EURASIP J. Adv. Signal Process. 2020 (1) (2020)
Sangyul Lee, Hee-Seok Oh
Robust Multivariate Regression on Riemannian Manifolds. DSAA (2020)
Hee-Seok Oh, Donghoh Kim
Image decomposition by bidimensional ensemble patch transform. Pattern Recognit. Lett. 135 (2020)
Ha Young Shin, Hee-Seok Oh
Robust Geodesic Regression. CoRR (2020)
Joonpyo Kim, Hee-Seok Oh
Pseudo-quantile functional data clustering. J. Multivar. Anal. 178 (2020)
Yaeji Lim, Hee-Seok Oh, Ying-Kuen K. Cheung
Multiscale Clustering for Functional Data. J. Classif. 36 (2) (2019)
Guebin Choi, Hee-Seok Oh, Donghoh Kim
Enhancement of variational mode decomposition with missing values. Signal Process. 142 (2018)
Dongik Jang, Hee-Seok Oh, Philippe Naveau
Identifying local smoothness for spatially inhomogeneous functions. Comput. Stat. 32 (3) (2017)
Yunfei Chen, Hee-Seok Oh
Spectrum measurement modelling and prediction based on wavelets. IET Commun. 10 (16) (2016)
Donghoh Kim, Hee-Seok Oh
Intrinsic Pattern Preserving Boundary Treatment Method for Empirical Mode Decomposition. Adv. Data Sci. Adapt. Anal. 8 (2) (2016)
Yunfei Chen, Hee-Seok Oh
A Survey of Measurement-Based Spectrum Occupancy Modeling for Cognitive Radios. IEEE Commun. Surv. Tutorials 18 (1) (2016)
Yaeji Lim, Hee-Seok Oh
Simultaneous confidence interval for quantile regression. Comput. Stat. 30 (2) (2015)
Minsu Park, Donghoh Kim, Hee-Seok Oh
Quantile-Based Empirical Mode Decomposition: An Efficient Way to Decompose Noisy Signals. IEEE Trans. Instrum. Meas. 64 (7) (2015)
Youngjo Lee, Hee-Seok Oh
A new sparse variable selection via random-effect model. J. Multivar. Anal. 125 (2014)
Jaeyong Lee, Hee-Seok Oh
Bayesian regression based on principal components for high-dimensional data. J. Multivar. Anal. 117 (2013)
Minjeong Park, Sinsup Cho, Hee-Seok Oh
The role of functional data analysis for instantaneous frequency estimation. Comput. Stat. 28 (5) (2013)
Donghoh Kim, Minjeong Park, Hee-Seok Oh
Bidimensional Statistical Empirical Mode Decomposition. IEEE Signal Process. Lett. 19 (4) (2012)
Donghoh Kim, Kyungmee O. Kim, Hee-Seok Oh
Extending the Scope of Empirical Mode Decomposition by Smoothing. EURASIP J. Adv. Signal Process. 2012 (2012)
Minjeong Park, Donghoh Kim, Hee-Seok Oh
A Reinterpretation of EMD by cubic spline interpolation. Adv. Data Sci. Adapt. Anal. 3 (4) (2011)
Dongik Jang, Hee-Seok Oh
Enhancement of spatially adaptive smoothing splines via parameterization of smoothing parameters. Comput. Stat. Data Anal. 55 (2) (2011)
Donghoh Kim, Hee-Seok Oh
EMD: A Package for Empirical Mode Decomposition and Hilbert Spectrum. R J. 1 (1) (2009)
Hee-Seok Oh, Donghoh Kim, Youngjo Lee
Cross-validated wavelet shrinkage. Comput. Stat. 24 (3) (2009)
Hee-Seok Oh, Donghoh Kim, Yongdai Kim
Robust wavelet shrinkage using robust selection of thresholds. Stat. Comput. 19 (1) (2009)
Kyungmee O. Kim, Hee-Seok Oh
Reliability functions estimated from commonly used yield models. Microelectron. Reliab. 48 (3) (2008)
Chun Gun Park, Hee-Seok Oh, Hakbae Lee
Bayesian selection of primary resolution and wavelet basis functions for wavelet regression. Comput. Stat. 23 (2) (2008)
Thomas C. M. Lee, Hee-Seok Oh
Robust penalized regression spline fitting with application to additive mixed modeling. Comput. Stat. 22 (1) (2007)
Donghoh Kim, Youngjo Lee, Hee-Seok Oh
Hierarchical-likelihood-based wavelet method for denoising signals with missing data. IEEE Signal Process. Lett. 13 (6) (2006)
Hee-Seok Oh, Thomas C. M. Lee
Hybrid local polynomial wavelet shrinkage: wavelet regression with automatic boundary adjustment. Comput. Stat. Data Anal. 48 (4) (2005)
Philippe Naveau, Hee-Seok Oh
Polynomial wavelet regression for images with irregular boundaries. IEEE Trans. Image Process. 13 (6) (2004)
Thomas C. M. Lee, Hee-Seok Oh
Automatic polynomial wavelet regression. Stat. Comput. 14 (4) (2004)
Ta-Hsin Li, Hee-Seok Oh
Wavelet spectrum and its characterization property for random processes. IEEE Trans. Inf. Theory 48 (11) (2002)