期刊名称：International Journal of Early Childhood Special Education
电子版ISSN：1308-5581
出版年度：2022
卷号：14
期号：3
页码：878-884
DOI：10.9756/INT-JECSE/V14I3.110
语种：English
出版社：International Journal of Early Childhood Special Education
摘要：In our research, we have used Convolution Neural Networks (CNN) to detect and identify the type of leaf as well as the disease it has been affected with. The image dataset we used for the training purpose is titled ‘Plant Village’. In this, the plant species were properly differentiated with respect to their species and disease they have been affected with. This image data was first made compatible with our CNN model by reducing its dimension to 227X227 pixels. The model was trained on various CNN layers to ensure that the features are extracted suitably. To deploy the model, we used stream lit web application python module. Here we could upload the leaf image and for our model to make a prediction. With our model, we were able to achieve an accuracy of above98%.
关键词：Convolution Neural Network;Dataset;Accuracy;Validation and Training
