Przybył, Krzysztof Damian

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Przybył, Krzysztof

Scientific title

dr hab.

ORCID

0000-0002-2535-8370

Faculty

Wydział Nauk o Żywności i Żywieniu

Department

Katedra Mleczarstwa i Inżynierii Procesowej

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2023 - 20257

Przybył, Krzysztof 7

Walkowiak, Katarzyna 3

Koszela, Krzysztof 2

Masewicz, Łukasz 2

Baranowska, Hanna Maria 1

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machine learning

blackcurrant powders 2

classifiers ensembles 2

gray-level co-occurrence matrix (GLCM) 2

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Now showing 1 - 7 of 7

2023
Interactions of Oleanolic Acid, Apigenin, Rutin, Resveratrol and Ferulic Acid with Phosphatidylcholine Lipid Membranes - A Spectroscopic and Machine Learning Study
Dwiecki, Krzysztof
Przybył, Krzysztof
Dezor, Dobrawa
Bąkowska, Ewa
Rocha, Silvia M.
2 2
2023
Fruit Powder Analysis Using Machine Learning Based on Color and FTIR-ATR Spectroscopy - Case Study: Blackcurrant Powders
Przybył, Krzysztof
Walkowiak, Katarzyna
Jedlińska, Aleksandra
Samborska, Katarzyna
Masewicz, Łukasz
Biegalski, Jakub
Pawlak, Tomasz
Koszela, Krzysztof
7 7
2024
Explainable AI: Machine Learning Interpretation in Blackcurrant Powders
Przybył, Krzysztof
54 13 54 13
2025
Machine Learning in Sensory Analysis of Mead—A Case Study: Ensembles of Classifiers
Przybył, Krzysztof
Cicha-Wojciechowicz Daria
Drabińska, Natalia
Majcher, Małgorzata Anna
20 20
2024
The Prediction of Pectin Viscosity Using Machine Learning Based on Physical Characteristics—Case Study: Aglupectin HS-MR
Siejak, Przemysław
Przybył, Krzysztof
Masewicz, Łukasz
Walkowiak, Katarzyna
Rezler, Ryszard
Baranowska, Hanna Maria
22 22
2023
Applications MLP and other methods in artificial intelligence of fruit and vegetable in convective and spray drying
Przybył, Krzysztof
Koszela, Krzysztof
8 8
2024
Efficiency of Identification of Blackcurrant Powders Using Classifier Ensembles
Przybył, Krzysztof
Walkowiak, Katarzyna
Kowalczewski, Przemysław Łukasz
60 4 60 4

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Interactions of Oleanolic Acid, Apigenin, Rutin, Resveratrol and Ferulic Acid with Phosphatidylcholine Lipid Membranes - A Spectroscopic and Machine Learning Study

Fruit Powder Analysis Using Machine Learning Based on Color and FTIR-ATR Spectroscopy - Case Study: Blackcurrant Powders

Explainable AI: Machine Learning Interpretation in Blackcurrant Powders

Machine Learning in Sensory Analysis of Mead—A Case Study: Ensembles of Classifiers

The Prediction of Pectin Viscosity Using Machine Learning Based on Physical Characteristics—Case Study: Aglupectin HS-MR

Applications MLP and other methods in artificial intelligence of fruit and vegetable in convective and spray drying

Efficiency of Identification of Blackcurrant Powders Using Classifier Ensembles