Przybył, K.;                     Gawrysiak-Witulska, M.;                     Bielska, P.;                     Rusinek, R.;                     Gancarz, M.;                     Dobrzański, B., Jr.;                     Siger, A.    
        Application of Machine Learning to Assess the Quality of Food Products—Case Study: Coffee Bean. Appl. Sci. 2023, 13, 10786.
    https://doi.org/10.3390/app131910786
    AMA Style
    
                                Przybył K,                                 Gawrysiak-Witulska M,                                 Bielska P,                                 Rusinek R,                                 Gancarz M,                                 Dobrzański B Jr.,                                 Siger A.        
                Application of Machine Learning to Assess the Quality of Food Products—Case Study: Coffee Bean. Applied Sciences. 2023; 13(19):10786.
        https://doi.org/10.3390/app131910786
    
    Chicago/Turabian Style
    
                                Przybył, Krzysztof,                                 Marzena Gawrysiak-Witulska,                                 Paulina Bielska,                                 Robert Rusinek,                                 Marek Gancarz,                                 Bohdan Dobrzański, Jr.,                                 and Aleksander Siger.        
                2023. "Application of Machine Learning to Assess the Quality of Food Products—Case Study: Coffee Bean" Applied Sciences 13, no. 19: 10786.
        https://doi.org/10.3390/app131910786
    
    APA Style
    
                                Przybył, K.,                                 Gawrysiak-Witulska, M.,                                 Bielska, P.,                                 Rusinek, R.,                                 Gancarz, M.,                                 Dobrzański, B., Jr.,                                 & Siger, A.        
        
        (2023). Application of Machine Learning to Assess the Quality of Food Products—Case Study: Coffee Bean. Applied Sciences, 13(19), 10786.
        https://doi.org/10.3390/app131910786