An Effectual Plant Leaf Disease Detection using Deep Learning Network with IoT Strategies
G. Ramkumar, Amirthalakshmi T.M, R. Prabu, A. Sabarivani
Abstract
Now-a-days the agriculture and the crops management is the crucial need to take care with, as well as the image processing industry provides lots of beneficiary terms against crops protection and support precaution needs. In this paper, a new Deep Learning methodology is introduced with respect to Internet of Things (IoT) strategy to attain best prediction results with proper accuracy, which it termed as Leaf Disease Estimation using Deep Learning Principle (LDEDLP). This proposed approach of LDEDLP adapts all latest technologies such as Internet of Things to identify the disease effectively from the plants and provides the sufficient alert to respective user. The proposed approach of LDEDLP identify the affected portion and segment that by using image segmentation strategy and apply the classification logic to estimate the category of disease. The proposed approach of LDEDLP provides high accuracy ratio with proper prediction results, in which all this proportions are explained clearly over the resulting section of this paper.