Rapid screening of mayonnaise quality using computer vision and machine learning

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F23%3A94484" target="_blank" >RIV/60460709:41210/23:94484 - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/record/display.uri?eid=2-s2.0-85147110219&origin=resultslist&sort=plf-f&src=s&sid=6a6e7181774f9485ef0685ff9da84525&sot=b&sdt=b&s=TITLE-ABS-KEY%28rapid+screening+mayonnaise+quality+computer+machine%29&sl=128&sessionSearchId=6a6e7181" target="_blank" >https://www.scopus.com/record/display.uri?eid=2-s2.0-85147110219&origin=resultslist&sort=plf-f&src=s&sid=6a6e7181774f9485ef0685ff9da84525&sot=b&sdt=b&s=TITLE-ABS-KEY%28rapid+screening+mayonnaise+quality+computer+machine%29&sl=128&sessionSearchId=6a6e7181</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11694-023-01814-x" target="_blank" >10.1007/s11694-023-01814-x</a>

Result language
angličtina
Original language name
Rapid screening of mayonnaise quality using computer vision and machine learning
Original language description
Implementing reliable, fast, and low-cost analysis is gaining popularity in the food industry. One alternative for this type of analysis is an artificial intelligence based on image analysis. This study aimed to use image analysis to develop classification models for discriminating the acceptability of mayonnaises. A semi-trained panel comprised of 8 evaluators classified 300 pictures of mayonnaises. Features extracted from the images include the mean, standard deviation,
Czech name
—
Czech description
—

Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
21101 - Food and beverages

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)