Peter Drotár

According to our database, Peter Drotár authored at least 32 papers between 2010 and 2023.

Collaborative distances:

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

2023

On the inter-dataset generalization of machine learning approaches to Parkinson's disease detection from voice.

Máté Hires, Peter Drotár, Nemuel Daniel Pah, Quoc Cuong Ngo, Dinesh Kant Kumar

Int. J. Medical Informatics, November, 2023

Feature Selection Based on a Sparse Neural-Network Layer With Normalizing Constraints.

Peter Bugata, Peter Drotár

IEEE Trans. Cybern., 2023

Bankruptcy prediction using ensemble of autoencoders optimized by genetic algorithm.

Róbert Kanász, Peter Gnip, Martin Zoricak, Peter Drotár

PeerJ Comput. Sci., 2023

End-To-End Deformable Attention Graph Neural Network for Single-View Liver Mesh Reconstruction.

Matej Gazda, Peter Drotár, Liset Vázquez Romaguera, Samuel Kadoury

Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Application of StyleGAN Architecture for Generating Venous Leg Ulcer Images.

David Jozef Hresko, Quoc Cuong Ngo, Rajna Ogrin, Peter Drotár, Elif Ekinci, Aye N. Tint, Dinesh K. Kumar

Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

2022

Multiple-Fine-Tuned Convolutional Neural Networks for Parkinson's Disease Diagnosis From Offline Handwriting.

Matej Gazda, Máté Hires, Peter Drotár

IEEE Trans. Syst. Man Cybern. Syst., 2022

Comparison of CNN-Learned vs. Handcrafted Features for Detection of Parkinson's Disease Dysgraphia in a Multilingual Dataset.

Zoltan Galaz, Peter Drotár, Jirí Mekyska, Matej Gazda, Jan Mucha, Vojtech Zvoncak, Zdenek Smékal, Marcos Faúndez-Zanuy, Reinel Castrillon, Juan Rafael Orozco-Arroyave, Steven Z. Rapcsak, Tamas Kincses, Lubos Brabenec, Irena Rektorová

Frontiers Neuroinformatics, 2022

Computerized analysis of speech and voice for Parkinson's disease: A systematic review.

Quoc Cuong Ngo, Mohammod Abdul Motin, Nemuel Daniel Pah, Peter Drotár, Peter Kempster, Dinesh K. Kumar

Comput. Methods Programs Biomed., 2022

Convolutional neural network ensemble for Parkinson's disease detection from voice recordings.

Máté Hires, Matej Gazda, Peter Drotár, Nemuel Daniel Pah, Mohammod Abdul Motin, Dinesh Kant Kumar

Comput. Biol. Medicine, 2022

Refined Mixup Augmentation for Diabetic Foot Ulcer Segmentation.

David Jozef Hresko, Jakub Vereb, Valentin Krigovsky, Michala Gayova, Peter Drotár

Proceedings of the Diabetic Foot Ulcers Grand Challenge - Third Challenge, 2022

Ensembled Autoencoder Regularization for Multi-structure Segmentation for Kidney Cancer Treatment.

David Jozef Hresko, Marek Kurej, Jakub Gazda, Peter Drotár

Proceedings of the Lesion Segmentation in Surgical and Diagnostic Applications, 2022

2021

Selective oversampling approach for strongly imbalanced data.

Peter Gnip, Liberios Vokorokos, Peter Drotár

PeerJ Comput. Sci., 2021

Self-Supervised Deep Convolutional Neural Network for Chest X-Ray Classification.

Matej Gazda, Ján Plávka, Jakub Gazda, Peter Drotár

IEEE Access, 2021

Mixup Augmentation for Kidney and Kidney Tumor Segmentation.

Matej Gazda, Peter Bugata, Jakub Gazda, David Hubacek, David Jozef Hresko, Peter Drotár

Proceedings of the Kidney and Kidney Tumor Segmentation - MICCAI 2021 Challenge, 2021

2020

On some aspects of minimum redundancy maximum relevance feature selection.

Peter Bugata, Peter Drotár

Sci. China Inf. Sci., 2020

2019

Weighted nearest neighbors feature selection.

Peter Bugata, Peter Drotár

Knowl. Based Syst., 2019

Ensemble feature selection using election methods and ranker clustering.

Peter Drotár, Matej Gazda, Liberios Vokorokos

Inf. Sci., 2019

Weighted k-nearest neighbors feature selection for high-dimensional multi-class data.

Peter Bugata, Peter Drotár

Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

Ensemble methods for strongly imbalanced data: bankruptcy prediction.

Peter Gnip, Peter Drotár

Proceedings of the 17th IEEE International Symposium on Intelligent Systems and Informatics, 2019

Stability analysis of WkNN feature selection.

Peter Bugata, Peter Gnip, Peter Drotár

Proceedings of the 13th IEEE International Symposium on Applied Computational Intelligence and Informatics, 2019

2018

Single-Class Bankruptcy Prediction Based on the Data from Annual Reports.

Peter Drotár, Peter Gnip, Martin Zoricak, Vladimír Gazda

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2018, 2018

2017

Tax optimization in an agent-based model of real-time spectrum secondary market.

Juraj Gazda, Viliam Kovác, Peter Tóth, Peter Drotár, Vladimír Gazda

Telecommun. Syst., 2017

Dynamic spectrum leasing and retail pricing using an experimental economy.

Juraj Gazda, Gabriel Bugár, Marcel Volosin, Peter Drotár, Denis Horváth, Vladimír Gazda

Comput. Networks, 2017

Comparison of Filter Techniques for Two-Step Feature Selection.

Peter Drotár, Slavomír Simonák, Emília Pietriková, Martin Chovanec, Eva Chovancová, Norbert Ádám, Csaba Szabó, Anton Baláz, Miroslav Binas

Comput. Informatics, 2017

2016

Evaluation of handwriting kinematics and pressure for differential diagnosis of Parkinson's disease.

Peter Drotár, Jirí Mekyska, Irena Rektorová, Lucia Masarová, Zdenek Smékal, Marcos Faúndez-Zanuy

Artif. Intell. Medicine, 2016

Spatial Real-Time Price Competition in the Dynamic Spectrum Access Markets.

Marcel Volosin, Juraj Gazda, Peter Drotár, Gabriel Bugár, Vladimír Gazda

Proceedings of the Multi-Agent Systems and Agreement Technologies, 2016

2015

An experimental comparison of feature selection methods on two-class biomedical datasets.

Peter Drotár, Juraj Gazda, Zdenek Smékal

Comput. Biol. Medicine, 2015

Contribution of different handwriting modalities to differential diagnosis of Parkinson's Disease.

Peter Drotár, Jirí Mekyska, Zdenek Smékal, Irena Rektorová, Lucia Masarová, Marcos Faúndez-Zanuy

Proceedings of the 2015 IEEE International Symposium on Medical Measurements and Applications, 2015

2014

Analysis of in-air movement in handwriting: A novel marker for Parkinson's disease.

Peter Drotár, Jirí Mekyska, Irena Rektorová, Lucia Masarová, Zdenek Smékal, Marcos Faúndez-Zanuy

Comput. Methods Programs Biomed., 2014

Fusion of diverse denoising systems for robust automatic speech recognition.

Naveen Kumar, Maarten Van Segbroeck, Kartik Audhkhasi, Peter Drotár, Shrikanth S. Narayanan

Proceedings of the IEEE International Conference on Acoustics, 2014

2013

A new modality for quantitative evaluation of Parkinson's disease: In-air movement.

Peter Drotár, Jirí Mekyska, Irena Rektorová, Lucia Masarová, Zdenek Smékal, Marcos Faúndez-Zanuy

Proceedings of the 13th IEEE International Conference on BioInformatics and BioEngineering, 2013

2010

Receiver technique for iterative estimation and cancellation of nonlinear distortion in MIMO SFBC-OFDM systems.

Peter Drotár, Juraj Gazda, Pavol Galajda, Dusan Kocur, Pavol Pavelka

IEEE Trans. Consumer Electron., 2010