Machine Learning Approach To Classify Mango

dc.contributor.authorAl Asif, Abu Abdullah
dc.contributor.authorRahman, MD Habibur
dc.date.accessioned2023-04-05T08:25:56Z
dc.date.available2023-04-05T08:25:56Z
dc.date.issued23-01-29
dc.description.abstractOur research titled "Machine Learning Approach To Classify Mango" is focusing the people not recognize mango species. Our work images in this research use deep learning, also known as machine learning. Python is used as a programming language because of how successfully it functions. Here we used raw data collect from Rajshahi. We are taken six different species of mangos. Here we have taken almost 1500 data. Data ratio 81% is train data and 19% is test data. We are using four algorithms from Transfer Learning Inception V3 95%, VGG19 74%, MobileNet 49%, and Convolutional Neural Networks (CNN) 90% provide test accuracy. Nobody else has performed this kind of mangos classification determination that I've seen.
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/10163
dc.identifier.urihttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/10163
dc.language.isoen_US
dc.publisherDaffodil International University
dc.sourceDIU Institutional Repository
dc.subjectMachine learning
dc.subjectProgramming language
dc.subjectNeural networks
dc.titleMachine Learning Approach To Classify Mango
dc.typeOther

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
22802.pdf
Size:
1.81 MB
Format:
Adobe Portable Document Format

Collections