Meat quality research using classification algorithms

Simple item page
dc.citation.epage32
dc.citation.issue2
dc.citation.journalTitleВимірювальна техніка та метрологія
dc.citation.spage29
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.authorKutyansky, Ostap
dc.contributor.authorPasternak, Volodymyr
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2025-03-13T08:43:20Z
dc.date.created2024-02-27
dc.date.issued2024-02-27
dc.description.abstractThe food industry is going through constant improvements and is subject to analyzing consumer needs, product quality research is essential to striking this balance. In this regard, meat quality, the most essential food category, should be studied with unbiased methods that give precise and correct results. Classification algorithms are considered one of the main components of developing an objective and reliable method of meat quality assessment. Such algorithms imply meat analysis and classification automation with many parameters in mind, which eventually gives a chance to make quick and correct decisions concerning its quality.
dc.format.extent29-32
dc.format.pages4
dc.identifier.citationKutyansky O. Meat quality research using classification algorithms / Kutyansky Ostap, Pasternak Volodymyr // Measuring Equipment and Metrology. — Lviv : Lviv Politechnic Publishing House, 2024. — Vol 85. — No 2. — P. 29–32.
dc.identifier.citationenKutyansky O. Meat quality research using classification algorithms / Kutyansky Ostap, Pasternak Volodymyr // Measuring Equipment and Metrology. — Lviv : Lviv Politechnic Publishing House, 2024. — Vol 85. — No 2. — P. 29–32.
dc.identifier.doidoi.org/10.23939/istcmtm2024.02.029
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/64145
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofВимірювальна техніка та метрологія, 2 (85), 2024
dc.relation.ispartofMeasuring Equipment and Metrology, 2 (85), 2024
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dc.relation.referencesen[3] O. R. Kutyansky and M. M. Mykyichuk, "Application of classification algorithms in quality control of meat products," in Abstr. XI Int. Scientific Practical Conf., Florence, Italy, Mar. 18-20, 2024. 2024. pp. 341-342. [Online]. Available: URL: https://eu-conf.com/en/events/quality-management-in-education-and-industry-experience-problems-and-prospects/
dc.relation.referencesen[4] Z. Keita. "Classification in machine learning: A guide for beginners"". Learn Data Science and AI Online | DataCamp. Date of access: April 22. 2024. [Online]. Available: https://www.datacamp.com/blog/classification-machine-learning.
dc.relation.referencesen[5] "Albumentations Documentation - What is image augmentation". Albumentations: fast and flexible image augmentations. Date of access: April 22. 2024. [Online]. Available: https://albumentations.ai/docs/introduction/image_augmentation/.
dc.relation.referencesen[6] I. M. Kobasa, L. M. Cheban, M. M. Vorobets, V. H. Yukalo, and M. Kukhtyn, Chemical and microbiological analysis of food products. Chernivtsi: Cherniv. nats. un-t, 2014. [Online]. Available: https://archer.chnu.edu.ua/bitstream/handle/123456789/3704/%D0%A5%D1%96%D0%BC%D1%96%D1%87%D0%BD%
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dc.relation.referencesen[8] N. Huynh. "Understanding loss functions for classification". Medium. Date of access: April 22. 2024. [Online]. Available: https://medium.com/@nghihuynh_37300/understanding-loss-functions-for-classification-81c19ee72c2a
dc.relation.referencesen[9] M. Dawood. "Introduction to classification algorithms". Medium. Date of access: April 22. 2024. [Online]. Available: https://muhammaddawoodaslam.medium.com/introduction-to-classification-algorithms-8e42b37adebf.
dc.relation.referencesen[10] L. Chen, S. Li, Q. Bai, J. Yang, S. Jiang, and Y. Miao, "Review of image classification algorithms based on convolutional neural networks", Remote Sens., vol. 13, no. 22, p. 4712, Nov. 2021. Accessed: May 2, 2024. [Online]. Available: https://doi.org/10.3390/rs13224712.
dc.relation.referencesen[11] M. Aladhadh, "A review of modern methods for the detection of foodborne pathogens", Microorganisms, vol. 11, no. 5, p. 1111, Apr. 2023. Accessed: May 2, 2024. [Online]. Available: https://doi.org/10.3390/microorganisms11051111.
dc.relation.referencesen[12] C. Xu, L. Kong, H. Gao, X. Cheng, and X. Wang, "A Review of Current Bacterial Resistance to Antibiotics in Food Animals", Frontiers Microbiol., vol. 13, May 2022. Accessed: May 2, 2024. [Online]. Available: https://doi.org/10.3389/fmicb.2022.822689.
dc.relation.referencesen[13] M. Hayes, "Measuring protein content in food: An overview of methods", Foods, vol. 9, no. 10, p. 1340, Sep. 2020. Accessed: May 2, 2024.[Online]. Available: https://doi.org/10.3390/foods9101340.
dc.relation.urihttps://datareportal.com/reports/digital-2024-global-overview-report
dc.relation.urihttps://doi.org/10.1111/1541-4337.13191
dc.relation.urihttps://eu-conf.com/en/events/quality-management-in-education-and-industry-experience-problems-and-prospects/
dc.relation.urihttps://www.datacamp.com/blog/classification-machine-learning
dc.relation.urihttps://albumentations.ai/docs/introduction/image_augmentation/
dc.relation.urihttps://archer.chnu.edu.ua/bitstream/handle/123456789/3704/%D0%A5%D1%96%D0%BC%D1%96%D1%87%D0%BD%
dc.relation.urihttps://library.nlu.edu.ua/POLN_TEXT/CUL/24-Metodi%20viznachennya%20falsif%20tovariv-Dubinina.pdf
dc.relation.urihttps://medium.com/@nghihuynh_37300/understanding-loss-functions-for-classification-81c19ee72c2a
dc.relation.urihttps://muhammaddawoodaslam.medium.com/introduction-to-classification-algorithms-8e42b37adebf
dc.relation.urihttps://doi.org/10.3390/rs13224712
dc.relation.urihttps://doi.org/10.3390/microorganisms11051111
dc.relation.urihttps://doi.org/10.3389/fmicb.2022.822689
dc.relation.urihttps://doi.org/10.3390/foods9101340
dc.rights.holder© Національний університет “Львівська політехніка”, 2024
dc.subjectMeat quality assessment
dc.subjectClassification algorithms
dc.subjectMachine learning
dc.subjectClassification
dc.titleMeat quality research using classification algorithms
dc.typeArticle

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Вимірювальна техніка та метрологія. – 2024. – Випуск 85, №2