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
Applications MLP and other methods in artificial intelligence of fruit and vegetable in convective and spray drying
Przybył, Krzysztof
Koszela, Krzysztof
8 8
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
Efficiency of Identification of Blackcurrant Powders Using Classifier Ensembles
Przybył, Krzysztof
Walkowiak, Katarzyna
Kowalczewski, Przemysław Łukasz
60 4 60 4
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
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

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

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

Efficiency of Identification of Blackcurrant Powders Using Classifier Ensembles

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

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