Abstract:
Depression My Project ‘PLANT DISEASE DETECTION USING CNN TECHNOLOGY’ works
with disease detection and identification for Grapevine, Strawberry based on image processing.
There is very big improvement was been made in the field of image preparing and Artificial
Intelligence and its applications are used in many different parts of designing. People have already
entered the time of digitalization. We caught pictures with the help of advanced cameras and the
more clear picture are produce then better ,useable and productive the result’s and outcome. In this
report I have done an arrangement of fresh, somewhere infected and fully sick leaves. I have been
utilizing the HSI shading model to make group of my properties and furthermore I have utilized
Neural Network (CNN) Tools for AI to investigate the outcomes. Although measurements for the
plant features are fundamental elements for plant science and research also related applications.
The information’s are related to plant features that principally useful for the applications used in
plant agricultural research and growth modeling also on farm production. Past direct measurement
methods are generally simple and not so much reliable, on the other hand they are very much time
consuming, cumbersome laborious. The proposed vision on the basis of methods that are efficient
in observing and detecting the exterior disease and other features. In this present state, image
processing algorithms are developing quickly, to detect plants diseases by recognizing and
identifying the particular color frame of the individual affected area. Eventually, the rotted area is
subdivide from an image. Then the area of decayed leaf chunk was deduced from the Grapevine
and Strawberry plants featured data. In my case, the outcomes have showed an encouraging
execution of this automated vision-based system, I have achieved 91% accuracy in practice with
complimentary validation.
