(untitled) (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Rice cultivation is one of the most important economic sectors for Indian economy. With the increase in world population, the demand for the rice cultivation is also increasing. In order to increase the growth of rice crop, it is necessary to detect the pests in an earlier stage to minimize the pest growth. But our farmers are still struggling to protect the crops from external threats particularly from insects in agricultural lands. To overcome this problem, we are providing a solution to protect the crops in the farming lands using deep networks. Hence, the lives of farmers are saved from their struggle. In this paper, we proposed a system that will help the farmers in detecting rice crop pest using deep convolutional neural network with VGG16 architecture. Then, the proposed model is compared with the existing models GoogleNet and AlexNet.