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ORCIDMariusz Wrzesien
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2020 – today
- 2024
[j3]Wladyslaw Homenda
, Agnieszka Jastrzebska, Witold Pedrycz, Mariusz Wrzesien:
Time series classification with their image representation. Neurocomputing 573: 127214 (2024)- 2023
- [c17]Milosz Wrzesien, Mariusz Wrzesien:
Classification of Time Series Using FCM-Based Forecasting Models. FUZZ 2023: 1-6 - [c16]Milosz Wrzesien, Mariusz Wrzesien, Wladyslaw Homenda:
Time Series Classification Using Images: The Case Of SAX-Like Transformation. ISD 2023 - 2022
- [c15]Milosz Wrzesien, Mariusz Wrzesien, Wladyslaw Homenda:
Time Series Processing with Cognitive Maps. The Case of General Forecast Modeling for Time Series of Similar Nature. FUZZ-IEEE 2022: 1-8 - [c14]Wladyslaw Homenda, Agnieszka Jastrzebska, Mariusz Wrzesien:
Time Series Classification Using Images. ISD 2022 - 2020
- [c13]Roman P. Bazylevych, Mariusz Wrzesien, Lubov Bazylevych:
A Set of Nets Planarization for Electronic Devices' Physical Design Automation. CSIT (1) 2020: 192-195
2010 – 2019
- 2019
- [j2]Mariusz Wrzesien, Waldemar Treder, Krzysztof Klamkowski, Witold R. Rudnicki:
Prediction of the apple scab using machine learning and simple weather stations. Comput. Electron. Agric. 161: 252-259 (2019) - [c12]Roman P. Bazylevych, Mariusz Wrzesien, Lubov Bazylevych:
Power System Islanding by the Hierarchical Clustering. CSIT (1) 2019: 145-148 - 2015
- [p1]Witold R. Rudnicki, Mariusz Wrzesien, Wieslaw Paja:
All Relevant Feature Selection Methods and Applications. Feature Selection for Data and Pattern Recognition 2015: 11-28 - 2013
- [j1]Agnieszka Podsiadlo, Mariusz Wrzesien, Wieslaw Paja, Witold R. Rudnicki, Bartek Wilczynski:
Active enhancer positions can be accurately predicted from chromatin marks and collective sequence motif data. BMC Syst. Biol. 7(S-6): S16 (2013) - [c11]Wieslaw Paja, Mariusz Wrzesien:
Melanoma important features selection using random forest approach. HSI 2013: 415-418 - 2012
- [c10]Krzysztof Pancerz, Wieslaw Paja, Mariusz Wrzesien, Jan Warchol:
Classification of Voice Signals through Mining Unique Episodes in Temporal Information Systems: A Rough Set Approach. CS&P 2012: 280-291 - [c9]Wieslaw Paja, Mariusz Wrzesien:
Decision Rules Development Using Set of Generic Operations Approach. ICDM 2012: 236-242 - 2011
- [c8]Pawel Cudek, Wieslaw Paja, Mariusz Wrzesien:
Automatic System for Classification of Melanocytic Skin Lesions Based on Images Recognition. ICMMI 2011: 189-196 - [c7]Pawel Cudek, Wieslaw Paja, Mariusz Wrzesien:
Image Recognition System for Diagnosis Support of Melanoma Skin Lesion. SIIS 2011: 217-225 - [c6]Wieslaw Paja, Mariusz Wrzesien:
Melanoma Diagnosis and Classification Web Center System: The Non-invasive Diagnosis Support Subsystem. ICDM 2011: 96-105 - [c5]Jerzy Gomula, Wieslaw Paja, Krzysztof Pancerz, Teresa Mroczek, Mariusz Wrzesien:
Experiments with Hybridization and Optimization of the Rules Knowledge Base for Classification of MMPI Profiles. ICDM 2011: 121-133 - [c4]Mariusz Wrzesien, Wieslaw Paja, Krzysztof Pancerz:
A Constructive Feature Induction Mechanism Founded on Evolutionary Strategies with Fitness Functions Generated on the Basis of Decision Trees. RSKT 2011: 89-94 - 2010
- [c3]Wieslaw Paja, Mariusz Wrzesien:
Medical Datasets Analysis: A Constructive Induction Approach. ICDM 2010: 442-449 - [c2]Wieslaw Paja, Krzysztof Pancerz, Mariusz Wrzesien:
A New Hybrid Method of Generation of Decision Rules Using the Constructive Induction Mechanism. RSKT 2010: 322-327
2000 – 2009
- 2005
- [c1]Zdzislaw S. Hippe, Jerzy W. Grzymala-Busse, Piotr Blajdo, Maksymilian Knap, Teresa Mroczek, Wieslaw Paja, Mariusz Wrzesien:
Classification of Medical Images in the Domain of Melanoid Skin Lesions. CORES 2005: 519-526
Coauthor Index
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