Smart System For Rotten Food

dc.AffiliationOctober University for modern sciences and Arts (MSA)  
dc.contributor.authorMohamed, Rana Mamdouh
dc.date.accessioned2021-01-27T07:59:34Z
dc.date.available2021-01-27T07:59:34Z
dc.date.issued2020
dc.descriptionComputer sciences distinguished graduation projects 2020en_US
dc.description.abstractClassification of fresh and rotten food such as fruits or vegetables is very important for families that have no time to check the food in their refrigerator daily and people who stock large quantities of the food like retailers. The project aims to classify between fresh and rotten food inside refrigerators using CNN, capturing the food by camera to classify if it is good or not. The images are labeled as fresh or rotten according to their physical appearance. A fruit has been chosen for this project(tomato or apple), they are RGB images, fresh and rotten images of the fruit. The results after training the model were very good as the accuracy reaches to 99% and the model could classify between the fresh and rotten fruit but the project was not applied to refrigerator due to the lake of images of food rot inside of it.en_US
dc.description.sponsorshipDr. Ahmed Farouken_US
dc.identifier.citationCopyright © 2021 MSA University. All Rights Reserved.en_US
dc.identifier.urihttp://repository.msa.edu.eg/xmlui/handle/123456789/4400
dc.language.isoenen_US
dc.publisherOctober University for Modern Sciences and Artsen_US
dc.relation.ispartofseriesCOMPUTER SCIENCES DISTINGUISHED PROJECTS 2020;
dc.subjectOctober University for Modern Sciences and Artsen_US
dc.subjectجامعة أكتوبر للعلوم الحديثة و الآدابen_US
dc.subjectUniversity of Modern Sciences and Artsen_US
dc.subjectMSA Universityen_US
dc.subjectSmart System Fooden_US
dc.titleSmart System For Rotten Fooden_US
dc.typeOtheren_US

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