Nutrient Deficiency Detection in Leaves using Deep Learning

Nutrient deficiency is major problem in the agricultural field and solutions available for this problem are not sufficient. Concept of Neural Network and Deep Learning can be used to solve such problem more efficiently. The nutrient deficiency detector is used for tracking the health of leaves. A data set was created to check the different features of leaves through deep learning modules and techniques. The user will have to input a leaf image. This image passes through various neural networks in order to look for the different deficiency features present in the leaf so as to determine the type of deficiency. The neural network will classify the image into its respective deficiency class. Once the state of the leaf was identified by the model, it let the user know about the nutrient shortage in the plant.