Identification of Diseases in Paddy Crops Using CNN
Keywords:
Paddy Crop, Leaf Smut, Bacterial Leaf Blight, Brown Spot, Convolution Neural Network, Deep Learning, Artificial IntelligenceAbstract
In ancient times, agriculture is one of the most predominant occupations of Indian civilizations and it has a great impact in contributing to our country’s economy. Unfortunately, due to several reasons like pests and unpredictable climatic conditions, there has been poor productivity in certain crops, especially paddy. This has been drawn attention towards enhancing the productivity of the paddy crops. Through lots of research, it has been identified that paddy crops are infected by various diseases, and this is one of the reasons that directly affects the overall productivity of the crop. Hence, there emerged an immediate need to take preventive measures and improve the overall productivity rate of paddy crop. In this regard, an Intelligent deep learning algorithm called Convolution Neural Network (CNN) is proposed with an increased structure of 15 layers which predict various diseases that may affect the rice leaves. The developed model efficiency was evaluated in terms of Accuracy, Precision, F-measure, and Recall.
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