Flower and leaf recognition for plant identification using convolutional neural network - Nurul FatihahSahidan; Ahmad Khairi Juha; Norasiah Mohammad; Zaidah Ibrahim (Institute of Advanced Engineering and Science, 2019)
This paper presents flower and leaf recognition for plant identification using Convolutional Neural Network (CNN). In this study, the performance of CNN for plant identification using images of the leaves, flowers and a combination of both are investigated. Two publicly available datasets, namely Folio leaf dataset and Flower Recognition dataset, have been used for the training and testing purposes. CNN has been proven to produce excellent results for object recognition but its performance can still be influenced by the type of images and the number of layers of the CNN architecture. Experimental results indicate that the utilization of leaf images only arrive to the highest accuracy for plant identification compared to the images of flowers only or the combination of both, that are 98%, 85% and 74%, respectively.