Abstract:
Carrot is a popular nutritious vegetable and cultivated throughout the world. But Farmers
still cultivating this vegetable without utilizing proper scientific technology. This may lead
to financial losses as well as reduce the profit of farmers. At present, vegetable disease
causes lots of financial and environmental problem. But, Early detection of vegetable
disease can reduce those losses and can make farmers smile. Hence, in our research we
have proposed a Deep Learning-based system for carrot disease recognition. we have
experimented with healthy carrot and three common carrot disease such as: Black rot,
Sclerotinia rot and Root knot. We have used Convolutional Neural Network (CNN) for
feature extraction purposes and fully connected neural network (FCNN) for disease
classification. Convolutional Neural Network is a great tool for image feature extraction,
and it reduces the hardship of manual feature extraction. We have experimented with
different convolutional model with different layer and our proposed Convolutional model
gives us accuracy of almost 94%, which is certainly helpful for the farmers to identify
carrot disease and maximize their benefit.
