Plant Classification based on Leaves using Artificial Neural Network


  • Vishwad Desai Nirma University
  • Vijay Savani Nirma University
  • Rutul Patel Nirma University


Artificial neural network, feature extraction, dimensionality reduction, classification, plant


Manual methods to examine leaf for plant classification can be tedious, therefore, automation is desired. Existing methods try distinctive approaches to accomplish this task. Nowadays, Convolution Neural Networks (CNN) are widely used for such application which achieves higher accuracy. However, CNN's are computationally expensive and require extensive dataset for training. Other existing methods are far less resource expensive but they also have their shortcomings for example, some features cannot be processed accurately with automation, some necessary differentiators are left out. To overcome this, we have proposed a simple Artificial Neural Network (ANN) for automatic classification of plants based on their leaf features. Experimental results show that the proposed algorithm able to achieve an accuracy of 96% by incorporating only a single hidden layer of ANN. Hence, our approach is fairly computationally efficient compared to existing CNN based methods


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How to Cite

Desai, V., Savani, V., & Patel, R. (2021). Plant Classification based on Leaves using Artificial Neural Network. International Journal of Integrated Engineering, 13(6), 39–49. Retrieved from