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Classification of Succulent Plant Using Convolutional Neural Network

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dc.contributor.author Hasan, Md. Zahid
dc.contributor.author Rakshit, Aniruddha
dc.contributor.author Das, Ashik Kumar
dc.contributor.author Iqbal, Md. Asif
dc.contributor.author Paul, Bidhan
dc.date.accessioned 2022-01-08T08:39:47Z
dc.date.available 2022-01-08T08:39:47Z
dc.date.issued 2020-07-30
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6685
dc.description.abstract Machine 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. en_US
dc.language.iso en_US en_US
dc.publisher Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Springer en_US
dc.subject Succulent plant en_US
dc.subject Convolutional en_US
dc.subject Neural network en_US
dc.subject Augmentation en_US
dc.subject Adam optimizer. en_US
dc.title Classification of Succulent Plant Using Convolutional Neural Network en_US
dc.type Article en_US


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