Hee-Seok Oh

According to our database, Hee-Seok Oh authored at least 45 papers between 2002 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Moving Sum Procedure for Change Point Detection under Piecewise Linearity.

Joonpyo Kim, Hee-Seok Oh, Haeran Cho

Technometrics, July, 2024

Novel sampling method for the von Mises-Fisher distribution.

Seungwoo Kang, Hee-Seok Oh

Stat. Comput., June, 2024

A data-adaptive dimension reduction for functional data via penalized low-rank approximation.

Yeonjoo Park, Hee-Seok Oh, Yaeji Lim

Stat. Comput., February, 2024

GSD: An R package for graph signal decomposition.

Hyeonglae Cho, Hee-Seok Oh, Donghoh Kim

SoftwareX, 2024

Decomposition via elastic-band transform.

Guebin Choi, Hee-Seok Oh

Pattern Recognit. Lett., 2024

Probabilistic Principal Curves on Riemannian Manifolds.

Seungwoo Kang, Hee-Seok Oh

IEEE Trans. Pattern Anal. Mach. Intell., 2024

2023

Zero-Inflated Time Series Clustering Via Ensemble Thick-Pen Transform.

Minji Kim, Hee-Seok Oh, Yaeji Lim

J. Classif., July, 2023

Robust spherical principal curves.

Jongmin Lee, Hee-Seok Oh

Pattern Recognit., June, 2023

Elastic-band transform for visualization and detection.

Guebin Choi, Hee-Seok Oh

Pattern Recognit. Lett., February, 2023

2022

Decomp2d: An R solution for image decomposition.

Hee-Seok Oh, Guebin Choi, Donghoh Kim

SoftwareX, 2022

spherepc: An R Package for Dimension Reduction on a Sphere.

Jongmin Lee, Jang-Hyun Kim, Hee-Seok Oh

R J., 2022

Robust Geodesic Regression.

Ha Young Shin, Hee-Seok Oh

Int. J. Comput. Vis., 2022

2021

EPT: An R package for ensemble patch transform.

Donghoh Kim, Hee-Seok Oh, Guebin Choi

SoftwareX, 2021

Principal component analysis in the wavelet domain.

Yaeji Lim, Junhyeon Kwon, Hee-Seok Oh

Pattern Recognit., 2021

Spherical Principal Curves.

Jongmin Lee, Jang-Hyun Kim, Hee-Seok Oh

IEEE Trans. Pattern Anal. Mach. Intell., 2021

2020

Image decomposition by bidimensional ensemble patch transform.

Hee-Seok Oh, Donghoh Kim

Pattern Recognit. Lett., 2020

Pseudo-quantile functional data clustering.

Joonpyo Kim, Hee-Seok Oh

J. Multivar. Anal., 2020

Ensemble patch transformation: a flexible framework for decomposition and filtering of signal.

Donghoh Kim, Guebin Choi, Hee-Seok Oh

EURASIP J. Adv. Signal Process., 2020

Robust Multivariate Regression on Riemannian Manifolds.

Sangyul Lee, Hee-Seok Oh

Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

2019

Multiscale Clustering for Functional Data.

Yaeji Lim, Hee-Seok Oh, Ying-Kuen K. Cheung

J. Classif., 2019

2018

Enhancement of variational mode decomposition with missing values.

Guebin Choi, Hee-Seok Oh, Donghoh Kim

Signal Process., 2018

2017

Identifying local smoothness for spatially inhomogeneous functions.

Dongik Jang, Hee-Seok Oh, Philippe Naveau

Comput. Stat., 2017

2016

Spectrum measurement modelling and prediction based on wavelets.

Yunfei Chen, Hee-Seok Oh

IET Commun., 2016

A Survey of Measurement-Based Spectrum Occupancy Modeling for Cognitive Radios.

Yunfei Chen, Hee-Seok Oh

IEEE Commun. Surv. Tutorials, 2016

Intrinsic Pattern Preserving Boundary Treatment Method for Empirical Mode Decomposition.

Donghoh Kim, Hee-Seok Oh

Adv. Data Sci. Adapt. Anal., 2016

2015

Quantile-Based Empirical Mode Decomposition: An Efficient Way to Decompose Noisy Signals.

Minsu Park, Donghoh Kim, Hee-Seok Oh

IEEE Trans. Instrum. Meas., 2015

Simultaneous confidence interval for quantile regression.

Yaeji Lim, Hee-Seok Oh

Comput. Stat., 2015

2014

A new sparse variable selection via random-effect model.

Youngjo Lee, Hee-Seok Oh

J. Multivar. Anal., 2014

2013

Bayesian regression based on principal components for high-dimensional data.

Jaeyong Lee, Hee-Seok Oh

J. Multivar. Anal., 2013

The role of functional data analysis for instantaneous frequency estimation.

Minjeong Park, Sinsup Cho, Hee-Seok Oh

Comput. Stat., 2013

2012

Bidimensional Statistical Empirical Mode Decomposition.

Donghoh Kim, Minjeong Park, Hee-Seok Oh

IEEE Signal Process. Lett., 2012

Extending the Scope of Empirical Mode Decomposition by Smoothing.

Donghoh Kim, Kyungmee O. Kim, Hee-Seok Oh

EURASIP J. Adv. Signal Process., 2012

2011

Enhancement of spatially adaptive smoothing splines via parameterization of smoothing parameters.

Dongik Jang, Hee-Seok Oh

Comput. Stat. Data Anal., 2011

A Reinterpretation of EMD by cubic spline interpolation.

Minjeong Park, Donghoh Kim, Hee-Seok Oh

Adv. Data Sci. Adapt. Anal., 2011

2009

Robust wavelet shrinkage using robust selection of thresholds.

Hee-Seok Oh, Donghoh Kim, Yongdai Kim

Stat. Comput., 2009

EMD: A Package for Empirical Mode Decomposition and Hilbert Spectrum.

Donghoh Kim, Hee-Seok Oh

R J., 2009

Cross-validated wavelet shrinkage.

Hee-Seok Oh, Donghoh Kim, Youngjo Lee

Comput. Stat., 2009

2008

Reliability functions estimated from commonly used yield models.

Kyungmee O. Kim, Hee-Seok Oh

Microelectron. Reliab., 2008

Bayesian selection of primary resolution and wavelet basis functions for wavelet regression.

Chun Gun Park, Hee-Seok Oh, Hakbae Lee

Comput. Stat., 2008

2007

Robust penalized regression spline fitting with application to additive mixed modeling.

Thomas C. M. Lee, Hee-Seok Oh

Comput. Stat., 2007

2006

Hierarchical-likelihood-based wavelet method for denoising signals with missing data.

Donghoh Kim, Youngjo Lee, Hee-Seok Oh

IEEE Signal Process. Lett., 2006

2005

Hybrid local polynomial wavelet shrinkage: wavelet regression with automatic boundary adjustment.

Hee-Seok Oh, Thomas C. M. Lee

Comput. Stat. Data Anal., 2005

2004

Polynomial wavelet regression for images with irregular boundaries.

Philippe Naveau, Hee-Seok Oh

IEEE Trans. Image Process., 2004

Automatic polynomial wavelet regression.

Thomas C. M. Lee, Hee-Seok Oh

Stat. Comput., 2004

2002

Wavelet spectrum and its characterization property for random processes.

Ta-Hsin Li, Hee-Seok Oh

IEEE Trans. Inf. Theory, 2002