Classification of Succulent Plant Using Convolutional Neural Network

dc.contributor.authorDas, Ashik Kumar
dc.contributor.authorIqbal, Md. Asif
dc.contributor.authorPaul, Bidhan
dc.contributor.authorRakshit, Aniruddha
dc.contributor.authorHasan, Md. Zahid
dc.date.accessioned2021-08-19T09:02:02Z
dc.date.available2021-08-19T09:02:02Z
dc.date.issued2020-07-30
dc.description.abstractMachine learning methods such as deep neural networks have remarkably improved plant species classification in recent years. It is very challenging task to classify plant species based on their categories. In this work, deep learning approach is explained to identify and classify succulent plant species using VGG19, three layers CNN and five layers CNN network on our dataset. The proposed architecture achieved a significant result from VGG19 and three layers CNN model. In succulent plant image dataset, there are 10 different classes of succulent and non-succulent plants. The dataset consists of 3632 succulent plant images and 200 non-succulent plant images. The model achieved 99.77% accuracy which performs better than VGG19 and three layers CNN model
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6017
dc.identifier.urihttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6017
dc.language.isoen_US
dc.publisherLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Springer
dc.sourceDIU Institutional Repository
dc.subjectSucculent plant
dc.subjectAugmentation
dc.subjectAdam optimizer
dc.subjectConvolutional neural network
dc.titleClassification of Succulent Plant Using Convolutional Neural Network
dc.typeArticle

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