Detection of fish freshness using artificial intelligence methods-Reference-Cited by-同舟云学术

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Detection of fish freshness using artificial intelligence methods

Published:2023-04-27 Issue:8 Volume:249 Page:1979-1990
ISSN:1438-2377
Container-title:European Food Research and Technology
language:en
Short-container-title:Eur Food Res Technol

Author:

Yasin Elham Tahsin,Ozkan Ilker Ali,Koklu Murat

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Biochemistry,General Chemistry,Food Science,Biotechnology

Link

https://link.springer.com/content/pdf/10.1007/s00217-023-04271-4.pdf

Reference60 articles.

1. Dutta MK, Issac A, Minhas N, Sarkar B (2016) Image processing based method to assess fish quality and freshness. J Food Eng 177:50–58. https://doi.org/10.1016/j.jfoodeng.2015.12.018

2. MohammadiLalabadi H, Sadeghi M, Mireei SA (2020) Fish freshness categorization from eyes and gills color features using multi-class artificial neural network and support vector machines. Aquacult Eng. https://doi.org/10.1016/j.aquaeng.2020.102076

3. Jose JA, Kumar CS, Sureshkumar S (2022) Tuna classification using super learner ensemble of region-based CNN-grouped 2D-LBP models. Inform Process Agric 9(1):68–79. https://doi.org/10.1016/j.inpa.2021.01.001

4. Erasmus VN, Kadhila T, Thyberg K, Kamara EN, Bauleth-D’Almeida G (2021) Public perceptions and factors affecting domestic marine fish consumption in Namibia, southwestern Africa. Region Stud Marine Sci. https://doi.org/10.1016/j.rsma.2021.101921

5. Prabhakar PK, Vatsa S, Srivastav PP, Pathak SS (2020) A comprehensive review on freshness of fish and assessment: analytical methods and recent innovations. Food Res Int 133:109157. https://doi.org/10.1016/j.foodres.2020.109157

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