Application of Convolutional Neural Networks (CNNs) in Agriculture

Abstract

AI and machine learning applications are on the rise. Especially, deep learning is used very frequently in research these days. Convolutional Neural Networks (CNNs) are one such popularly used deep

learning approach in the agricultural domain. In smart agriculture, CNNs find its use in identification, classification and mapping problems. It is used for disease & weed: identification and classification. It is also utilized for crop yield prediction. Its combination with IoT and Drone devices enhances its application perspectives. Hence, this paper provides insights into the CNN methodology. It reviews the available datasets and the effectiveness of existing CNN application in the agricultural domain.