Machine Learning Approach To Classify Mango

dc.contributor.author	Al Asif, Abu Abdullah
dc.contributor.author	Rahman, MD Habibur
dc.date.accessioned	2023-04-05T08:25:56Z
dc.date.available	2023-04-05T08:25:56Z
dc.date.issued	23-01-29
dc.identifier.uri	http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/10163
dc.description.abstract	Our 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.	en_US
dc.language.iso	en_US	en_US
dc.publisher	Daffodil International University	en_US
dc.subject	Machine learning	en_US
dc.subject	Programming language	en_US
dc.subject	Neural networks	en_US
dc.title	Machine Learning Approach To Classify Mango	en_US
dc.type	Other	en_US