Transfer Learning Models for the Plant Disease Detection

Abstract

Digital Image Processing based Multimedia system has become a basic component of information field. Detecting the infected plants in exact way and on time is challenging task to get exact horticulture. Preventing the excessively waste of monetary and different assets prompts gains the solid efficiency. The essential task is to prevent the infections in the varied climate so that the ailments are diagnosed ahead of time and precisely. The diagnosis of diseases happened on plants is carried out utilizing a few techniques. The plant disease detection technique is proposed in this research work. The proposed model is based on transfer learning which is the combination of VGG16 and CNN. The proposed model is implemented in python and results is analyzed in terms of accuracy, precision and recall.