Maize leaf disease classification using convolutional neural network

Agriculture faces a variety of maize diseases that farmers are unable to identify them. Diseases grow from day and many crops will die due lack proper treatment also failing in finding what kind disease it has been. The most common Common rust, Northern leaf grey spot, Blight etc. Examining the plant with bare eyes identifying result imprecise detection diseases. This, turn lead inappropriate usage pesticide causes harmful chronic human beings. So, automatic accurate identification is essential food security. Society can produce enough meet demand using recent technologies. application digital technologies may save time protect decaying well advance. Hence, an idea for detecting affected automatically be more useful farmers. Deep learning recently grabbed attention researchers helped develop system image classification. deep techniques its variants have great potential modern agriculture. main focus this article on fine-tuning evaluation Convolutional Neural Networks (CNN) image-based leaves In work, CNN used detect classify order increase accuracy detection, AlexNet architecture disease. CNN, 87% architecture, 98.5% achieved.