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Drumstick Leaf Detection by Machine Learning Approach

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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


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