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2020 – today
- 2022
[c10]Ryszard Leniowski, Lucyna Leniowska
, Michal Wronski, Krzysztof Tomecki, Marcin Grochowina, Lukasz Ryk:
Intelligent candidate recommendation system based on experimental calculation of the similarity model. FUZZ-IEEE 2022: 1-7- 2021
- [c9]Marcin Grochowina, Lucyna Leniowska:
Applying DCT Combined Cepstrum for the Assessment of the Arteriovenous Fistula Condition. ICCS (3) 2021: 684-692
2010 – 2019
- 2019
- [c8]Marcin Grochowina, Kamil Wojnar, Lucyna Leniowska:
An application of wavelet transform for non-invasive evaluation of arteriovenous fistula state. SPA 2019: 214-217 - [c7]Dorota Gil, Marcin Grochowina, Lucyna Leniowska:
Detecting of the rolling bearing state based on acoustic signal and the k-NN classifier. SPA 2019: 246-249 - 2018
- [c6]Krzysztof Krupa, Marcin Grochowina:
Microprocessor implementation of the sound source location process based on the correlation of signals. SPA 2018: 59-63 - [c5]Marcin Grochowina, Lucyna Leniowska:
Design and implementation of a device supporting automatic diagnosis of arteriovenous fistula. SPA 2018: 186-190 - 2017
- [c4]Marcin Grochowina, Lucyna Leniowska:
Analysys of the impact of disturbance on the arteriovenous fistula state classification. FedCSIS (Communication Papers) 2017: 51-55 - 2016
- [c3]Marcin Grochowina, Lucyna Leniowska:
The new method of the selection of features for the k-NN classifier in the arteriovenous fistula state estimation. FedCSIS 2016: 281-285 - 2015
- [c2]Marcin Grochowina, Lucyna Leniowska:
Comparison of SVM and k-NN classifiers in the estimation of the state of the arteriovenous fistula problem. FedCSIS 2015: 249-254 - 2014
- [c1]Marcin Grochowina, Lucyna Leniowska, Piotr Dulkiewicz:
Application of Artificial Neural Networks for the Diagnosis of the Condition of the Arterio-venous Fistula on the Basis of Acoustic Signals. Brain Informatics and Health 2014: 400-411
Coauthor Index
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