Drumstick Leaf Detection by Machine Learning Approach

dc.contributor.author	Nasrullah, Md
dc.date.accessioned	2023-03-13T06:25:06Z
dc.date.available	2023-03-13T06:25:06Z
dc.date.issued	23-01-29
dc.identifier.uri	http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/9917
dc.description.abstract	This project titled “Drumstick Leaf Detection by Machine Learning Approach “. The traditional method of image recognition is to extract features manually, which cannot solve this problem well due to the complex background of and the taro plants similarity between their categories. With the advancement of science and technology. This work will help us to detect different flowers. I used deep learning algorithms like CNN, INCEPTION V3, RESNET50, RESNET152V2, VGG19, and MOBILE NET to detect 3 different types of water lilies. I achieved 100% accuracy at RESNET152V2, 97% accuracy at INCEPTIONV3, 99% at VGG19, and 99% at MOBILE NET. My system also achieved 81% accuracy at RESNET50.	en_US
dc.language.iso	en_US	en_US
dc.publisher	Daffodil International University	en_US
dc.subject	Traditional	en_US
dc.subject	Technology	en_US
dc.subject	Deep Learning	en_US
dc.subject	Algorithms	en_US
dc.title	Drumstick Leaf Detection by Machine Learning Approach	en_US
dc.type	Other	en_US