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Paper Details


Title
Classification of succulent plant using convolutional neural network
Author
Ashik Kumar Das, Aniruddha Rakshit, Bidhan Paul, Md. Asif Iqbal, Md. Zahid Hasan,
Email
aniruddha.cse@diu.edu.bd
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.

Keywords
Succulent plant Convolutional Neural Network Augmentation Adam optimizer
Journal or Conference Name
Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Publication Year
2020
Indexing
scopus