DSpace Repository

Detecting Bangladeshi flowers and its classifications from image using CNN

Show simple item record

dc.contributor.author Fariha, Tahmina Tabassom
dc.contributor.author Tipu, Md.Atikul Islam
dc.date.accessioned 2025-08-28T07:01:31Z
dc.date.available 2025-08-28T07:01:31Z
dc.date.issued 2024-08-24
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14024
dc.description Project report en_US
dc.description.abstract Image processing has been one of the most practiced features of digitalization and it has enormous role in different sectors of our life. Convolutional Neural Network (CNN) has made image processing and other mechanism related to images much more significant and glorious. We captured images of flowers in different angles with different shades and nature mode so that while analyzing it can call on enormous data even if candid image is taken in testing purpose. We went through MobileNet, InceptionV3, and VGG16 models to find the best suited one and that will be automatically called by the system and with that algorithm the rest analysis will occur. We found 95.39% accuracy for MobileNet. The rest InceptionV3 and VGG16 have 94.68% and 92.24% accuracy respectively. This will be very much beneficial to know about our native nation and its resources and such dataset is rarely found on web when we insist about Bangladesh. en_US
dc.description.sponsorship DIU en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Image Classification en_US
dc.subject Accuracy and Precision en_US
dc.subject Convolutional Neural Network (CNN) en_US
dc.title Detecting Bangladeshi flowers and its classifications from image using CNN 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