DSpace Repository

Fresh and Rotten Fruit Classification Using Deep Learning

Show simple item record

dc.contributor.author Hasan, MD Mehedi
dc.contributor.author Hasan, MD Moinul
dc.date.accessioned 2022-01-20T07:03:22Z
dc.date.available 2022-01-20T07:03:22Z
dc.date.issued 2021-06-02
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6844
dc.description.abstract Fruit cultivation has been a traditional part of the agricultural practices in Bangladesh. There has been a revolution in fruit farming. From fruits we get nutrition. It is a source of vitamins and minerals. Sometimes fruits are rotten in the consumer end also the packing end.so, to avoid these rotten fruits we came up with this research work. In the recent advancements of computer vision & deep learning our approach is to recognize whether a fruit is fresh or rotten. Now the whole lot have become smart and generation dependent. We can see the usage of AI and gadget learning everywhere. Following this, I constructed right here a device. A device this is smart, fast and that device can perceive clean and rotten fruits. I use right here python CNN version to classifying the rotten fruit and clean fruit. This device can perceive the share of rotten and freshness of fruit by the use of photograph data. This device could make our paintings easy with massive farm and juice manufacturing unit to perceive rotted fruit. We wish that it's going to make our paintings extra correct in much less time. en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Organic cultivation en_US
dc.subject Agricultural systems en_US
dc.title Fresh and Rotten Fruit Classification Using Deep Learning en_US
dc.type Other en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Browse

My Account

Statistics