Abstract:
Rice is one of the major developed crops in Bangladesh which is influenced by different
infections at different stages of its cultivation. It is exceptionally troublesome for the
farmers to manually identify these infections precisely with their constrained knowledge.
Recent improvements in Profound Learning appear that Automatic Image
Acknowledgment frameworks utilizing Convolutional Neural Network (CNN) models can
be exceptionally advantageous in such issues. Since rice leaf malady picture dataset is not
effortlessly accessible, we have created our possess dataset which is little in measure
subsequently we have used Transfer Learning to create our profound learning show. I use
primary data which are collected from different cultivation field in Tangail. The proposed
CNN engineering is based on InceptionResnetV2 and is trained and tried on the dataset
collected from rice areas. The exactness of the proposed demonstrate is 93.12%.
