Smart System For Rotten Food
dc.Affiliation | October University for modern sciences and Arts (MSA) | |
dc.contributor.author | Mohamed, Rana Mamdouh | |
dc.date.accessioned | 2021-01-27T07:59:34Z | |
dc.date.available | 2021-01-27T07:59:34Z | |
dc.date.issued | 2020 | |
dc.description | Computer sciences distinguished graduation projects 2020 | en_US |
dc.description.abstract | Classification 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.sponsorship | Dr. Ahmed Farouk | en_US |
dc.identifier.citation | Copyright © 2021 MSA University. All Rights Reserved. | en_US |
dc.identifier.uri | http://repository.msa.edu.eg/xmlui/handle/123456789/4400 | |
dc.language.iso | en | en_US |
dc.publisher | October University for Modern Sciences and Arts | en_US |
dc.relation.ispartofseries | COMPUTER SCIENCES DISTINGUISHED PROJECTS 2020; | |
dc.subject | October University for Modern Sciences and Arts | en_US |
dc.subject | جامعة أكتوبر للعلوم الحديثة و الآداب | en_US |
dc.subject | University of Modern Sciences and Arts | en_US |
dc.subject | MSA University | en_US |
dc.subject | Smart System Food | en_US |
dc.title | Smart System For Rotten Food | en_US |
dc.type | Other | en_US |