Jan Vrba

Orcid: 0000-0002-3538-7124

Affiliations:
  • University of Chemistry and Technology Prague, Faculty of Chemical Engineering, Prague, Czech Republic


According to our database1, Jan Vrba authored at least 12 papers between 2016 and 2024.

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Bibliography

2024
Reproducible Machine Learning-based Voice Pathology Detection: Introducing the Pitch Difference Feature.
CoRR, 2024

Application of Deep Learning Models for Vocal Cords Detection in Laryngoscopic Imagery.
Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 28th International Conference KES-2024, 2024

Comparative Analysis of YOLO-based Models for Vocal Cord Segmentation in Laryngoscopic Images.
Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 28th International Conference KES-2024, 2024

Improving Voice Pathology Classification Using Artificial Data Generation.
Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 28th International Conference KES-2024, 2024

2023
Hydrogel Microrobots Self-Assembled into Ordered Structures with Programmable Actuation.
Adv. Intell. Syst., September, 2023

2022
Padasip: An open-source Python toolbox for adaptive filtering.
J. Comput. Sci., 2022

2021
An automated platform for assembling light-powered hydrogel microrobots and their subsequent chemical binding.
J. Comput. Sci., 2021

A Machine Learning Approach for Gearbox System Fault Diagnosis.
Entropy, 2021

2020
Introduction to Extreme Seeking Entropy.
Entropy, 2020

An Automated Platform for Microrobot Manipulation.
Proceedings of the 15th International Conference on Soft Computing Models in Industrial and Environmental Applications, 2020

2016
Feature selection via competitive levy flights.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Study of Learning Entropy for onset detection of epileptic seizures in EEG time series.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016


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