Vangelis P. Oikonomou

发表

A Novel Compressive Sensing Scheme under the Variational Bayesian Framework

Yiannis Kompatsiaris, Vangelis P. Oikonomou, Spiros Nikolopoulos, 2019, 2019 27th European Signal Processing Conference (EUSIPCO).

Steady state visual evoked potential detection using Subclass Marginal Fisher Analysis

Yiannis Kompatsiaris, Anastasios Maronidis, Vangelis P. Oikonomou, 2017, 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER).

BCIs using steady-state visual-evoked potentials

Ioannis Kompatsiaris, Vangelis P. Oikonomou, Spiros Nikolopoulos, 2020 .

Sparse Kernel Machines for motor imagery EEG classification

Yiannis Kompatsiaris, Vangelis P. Oikonomou, Spiros Nikolopoulos, 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

A sparse linear model for the analysis of fMRI data with non stationary noise

Dimitrios I. Fotiadis, Vangelis P. Oikonomou, Evanthia E. Tripoliti, 2009, 2009 4th International IEEE/EMBS Conference on Neural Engineering.

Robust Motor Imagery Classification Using Sparse Representations and Grouping Structures

Ioannis Kompatsiaris, Vangelis P. Oikonomou, Spiros Nikolopoulos, 2020, IEEE Access.

An adaptive method for the recovery of missing samples from FHR time series

Lenka Lhotská, Vangelis P. Oikonomou, Chrysostomos D. Stylios, 2013, Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems.

Motor Imagery Classification via Clustered-Group Sparse Representation

Vangelis P. Oikonomou, Yiannis Kompatsiaris, Spiros Nikolopoulos, 2019, 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE).

A sparse variational Bayesian approach for fMRI data analysis

Dimitrios I. Fotiadis, Vangelis P. Oikonomou, Evanthia E. Tripoliti, 2008, 2008 8th IEEE International Conference on BioInformatics and BioEngineering.

A Comparison Study on EEG Signal Processing Techniques Using Motor Imagery EEG Data

Yiannis Kompatsiaris, Vangelis P. Oikonomou, Spiros Nikolopoulos, 2017, 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS).

Sparse Bayesian Learning for Multiclass Classification with Application to SSVEP- BCI

Yiannis Kompatsiaris, Vangelis P. Oikonomou, Spiros Nikolopoulos, 2017, GBCIC.

A Novel Regression-based Algorithm for the recognition of SSVEP responses

Vangelis P. Oikonomou, Yiannis Kompatsiaris, Spiros Nikolopoulos, 2020, 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE).

Identification of Brain Functional Networks Using a Model-Based Approach

Vangelis P. Oikonomou, Konstantinos Blekas, Loukas G. Astrakas, 2019, Int. J. Pattern Recognit. Artif. Intell..

Erratum: Automatic Evaluation of FHR Recordings from CTU-UHB CTG Database

Vangelis P. Oikonomou, Chrysostomos D. Stylios, Petros Karvelis, 2013, ICIT 2013.

Resting state fMRI analysis using a spatial regression mixture model

Vangelis P. Oikonomou, Konstantinos Blekas, Loukas Astrakas, 2013, 13th IEEE International Conference on BioInformatics and BioEngineering.

KNOWLEDGE-BASED SYSTEMS FOR ARRHYTHMIA DETECTION AND CLASSIFICATION

Dimitrios I. Fotiadis, Vangelis P. Oikonomou, M. G. Tsipouras, 2004 .

A template-based method for the estimation of Event Related Potentials using the Bayesian linear model

Dimitrios I. Fotiadis, Vangelis P. Oikonomou, 2009, 2009 16th International Conference on Digital Signal Processing.

Bayesian Methods for fMRI Time-Series Analysis Using a Nonstationary Model for the Noise

Dimitrios I. Fotiadis, Vangelis P. Oikonomou, Evanthia E. Tripoliti, 2010, IEEE Transactions on Information Technology in Biomedicine.

Automatic Evaluation of FHR Recordings from CTU-UHB CTG Database

Lenka Lhotská, Vangelis P. Oikonomou, Chrysostomos D. Stylios, 2013, ITBAM.

Functional Connectivity in Parkinson Disease Through Mixture Modelling

Vangelis P. Oikonomou, Loukas Astrakas, Kostas Blekas, 2018, 2018 IEEE 13th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP).

Sparse EEG Source Localization Under the Variational Bayesian Framework

Vangelis P. Oikonomou, Yiannis Kompatsiaris, Y. Kompatsiaris, 2019, 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE).

A Sparse and Spatially Constrained Generative Regression Model for fMRI Data Analysis

Vangelis P. Oikonomou, Konstantinos Blekas, Loukas Astrakas, 2012, IEEE Transactions on Biomedical Engineering.

Sparse Bayesian Learning for subject independent classification with application to SSVEP-BCI

Yiannis Kompatsiaris, Anastasios Maronidis, Vangelis P. Oikonomou, 2017, 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER).

A Novel Bayesian Approach for EEG Source Localization

Ioannis Kompatsiaris, Vangelis P. Oikonomou, Y. Kompatsiaris, 2020, Comput. Intell. Neurosci..

An Adaptive Regression Mixture Model for fMRI Cluster Analysis

Vangelis P. Oikonomou, Konstantinos Blekas, K. Blekas, 2013, IEEE Transactions on Medical Imaging.

Comparative evaluation of state-of-the-art algorithms for SSVEP-based BCIs pdf

Yiannis Kompatsiaris, Vangelis P. Oikonomou, Elisavet Chatzilari, 2016, ArXiv.

A Kalman filter based methodology for EEG spike enhancement

Dimitrios I. Fotiadis, Vangelis P. Oikonomou, Alexandros T. Tzallas, 2007, Comput. Methods Programs Biomed..

Discrimination of SSVEP responses using a kernel based approach

Yiannis Kompatsiaris, Vangelis P. Oikonomou, Spiros Nikolopoulos, 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Dimitrios I. Fotiadis, Vangelis P. Oikonomou, D. Fotiadis, 2010 .

Machine-learning techniques for EEG data

Ioannis Kompatsiaris, Vangelis P. Oikonomou, Spiros Nikolopoulos, 2020 .

A multimodal dataset for authoring and editing multimedia content: The MAMEM project

Steffen Staab, Ioulietta Lazarou, Ioannis Kompatsiaris, 2017, Data in brief.

A Sparse Spatial Linear Regression Model for fMRI Data Analysis

Vangelis P. Oikonomou, Konstantinos Blekas, 2010, SETN.

Sparse Graph-based Representations of SSVEP Responses Under the Variational Bayesian Framework

Yiannis Kompatsiaris, Vangelis P. Oikonomou, Spiros Nikolopoulos, 2021, 2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE).

Reconstructing EOG From EEG Timeseries: A Spatial Filtering Approach

Ioannis Kompatsiaris, Vangelis P. Oikonomou, Maria Panou, 2021, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

The MAMEM Project-A dataset for multimodal human-computer interaction using biosignals and eye tracking information

Ioulietta Lazarou, Ioannis Kompatsiaris, Vangelis P. Oikonomou, 2017 .

A bayesian spatio - temporal approach for the analysis of FMRI data with non - stationary noise

Dimitrios I. Fotiadis, Vangelis P. Oikonomou, Evanthia E. Tripoliti, 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.