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prof. Ing. Peter Drotár, PhD.

prof. Ing. Peter Drotár, PhD.

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Peter Drotár received M.Sc. and Ph.D. degrees in electronics from Technical University of Kosice, Slovakia in 2007 and 2010, respectively. From 2010 to 2012, he was with Honeywell International, Advanced Technology Europe as Scientist for Communication and Surveillance systems. From 2012 to 2015, he was with SIX research centre, Brno University of Technology as postdoctoral research assistant. He acted as a visiting researcher at University of Southern California, LA, USA, Ramon Llull University in Barcelona, ESP and Hamburg University of Technology, Hamburg-Harburg, GER. Currently, he is Associate Professor at the Department of Computers and Informatics, Technical University of Kosice.

Research interests:
  • Machine learning for handwriting and speech analysis
  • Bankruptcy prediction, decision support for digital business
  • Feature selection for big data
Projects:
Publications:

2023

D. J. Hreško; Q. C. Ngo; R. Ogrin; P. Drotár; E. Ekinci; A. N. Tint; D. K. Kumar

Application of StyleGAN Architecture for Generating Venous Leg Ulcer Images

Journal: 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

R. Kanász, P. Gnip, M. Zoričák, P. Drotár

Bankruptcy prediction using ensemble of autoencoders optimized by genetic algorithm

Journal: PeerJ. Computer science.

Q. C. Ngo, M. A. Motin, N. D. Pah, P. Drotár, P. Kempster, D. Kumar

Computerized analysis of speech and voice for parkinson's disease: a systematic review

Journal: Computer Methods and Programs in Biomedicine

M. Gazda, M. Hireš, P. Drotár

Ensemble of convolutional neural networks for Parkinson’s disease diagnosis from offline handwriting

Journal: The 20th Conference of the International Graphonomics Society.

D. J. Hreško, M. Kurej, J. Gazda, P. Drotár

Ensembled autoencoder regularization for multi-structure segmentation for kidney cancer treatment

Journal: Lesion Segmentation in Surgical and Diagnostic Applications

P. Bugata, P. Drotár

Feature selection based on a sparse neural-network layer with normalizing constraints

Journal: IEEE Transactions on Cybernetics.

M. Hireš, P. Drotár, N. D. Pah, Q. C. Ngo, D. K. Kumar

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

Journal: International Journal of Medical Informatics

D. J. Hreško, J. Vereb, V. Krigovsky, M. Gayová, P. Drotár

Refined mixup augmentation for diabetic foot ulcer segmentation

Journal: Diabetic Foot Ulcers Grand Challenge

2022

M. Hireš, P. Bugata, M. Gazda, D. J. Hreško, R. Kanász, L. Vavrek, P. Drotár

Brief Overview of Neural Networks for Medical Applications

Journal: Acta Electrotechnica et Informatica.

M. Hireš, M. Gazda, P. Drotár, N. D. Pah, M. A. Motin, D. K. Kumar

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

Journal: Computers in Biology and Medicine

M. Gazda, P. Bugata, J. Gazda, D. Hubacek, D. J. Hreško, P. Drotár

Mixup augmentation for kidney and kidney tumor segmentation

Journal: Kidney and Kidney Tumor Segmentation.

M. Gazda, M. Hireš, P. Drotár

Multiple-fine-tuned convolutional neural networks for parkinson’s disease diagnosis from offline handwriting

Journal: IEEE Transactions on Systems, Man, and Cybernetics

2021

L. Vavrek, M. Hireš, D. Kumar, P. Drotár

Deep convolutional neural network for detection of pathological speech

Journal: SAMI 2021

P. Drotár, M. Dobeš

Dysgraphia detection through machine learning

Journal: Scientific Reports.

P. Drotár, G. Bugár, J. Gazda

Inteligentné systémy v informatike

G. Bugár, J. Gazda, P. Drotár

Krátky úvod do počítačových sietí

P. Gnip, L. Vokorokos, P. Drotár

Selective oversampling approach for strongly imbalanced data

Journal: PeerJ. Computer science.

M. Gazda, J. Plavka, J. Gazda, P. Drotár

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

Journal: IEEE Access

2020

M. Zoričák, P. Gnip, P. Drotár, V. Gazda

Bankruptcy prediction for small- and medium-sized companies using severely imbalanced datasets

Journal: Economic Modelling

P. Gnip, P. Drotár

Ensemble methods for strongly imbalanced data: Bankruptcy prediction

Journal: 17th International Symposium on Intelligent Systems and Informatics

P. Drotár, P. Bugata

On some aspects of minimum redundancy maximum relevance feature selection

Journal: Science China Information Sciences. Roč. 63, č. 1 (2020), s. 1-15 [print].

M. Hireš, M. Molnárová, P. Drotár

Robustness of Interval Monge Matrices in Fuzzy Algebra

Journal: Mathematics.

P. Bugata, P. Gnip, P. Drotár

Stability analysis of WkNN feature selection

Journal: Applied Computational Intelligence and Informatics.