PLANT DISEASE DETECTION USING CNN

PLANT DISEASE DETECTION USING CNN

Ms.CHITTURI.CHAITANYA , Ms.BANDI.JAHNAVI , Mr.K.SIVAKUMAR

B.E Graduate(IV year) Computer Science and Engineering,SCSVMV,Kanchipuram,

B.E Graduate(IV year) Computer Science and Engineering,SCSVMV,Kanchipuram,

Assistant Professor,Computer Science and Engineering,SCSVMV,Kanchipuram

ABSTRACT:-
Crop production plays a significant role in the agricultural sector.The loss of food is primarily attributed to contaminated crops,which reflexively decreases the rate of development. Plant leaf disease has long and compromises its quality.Conventional methods of plant disease detection in naked eye observation methods and it is non-effective for large crops.Using digital image processing and machine learning the disease detection in plant is efficient,less time consuming and accurate.This technique saves time,efforts,labour and use of pesticides.Hope this approach will becomes a little contribution for agriculture fields.Accurate diagnosis of diseases has been a significant challenge and the recent advances in computer vision made possible by deep learning has paved the way for camera-assisted disease diagnosis for plant leaf. It described the innovative solution that provides efficient disease detection and deep learning with CNN has achieved great success in the classification of various plant leaf diseases.The developed model is able to recognize 38 different type of plant diseases out of 14 different plant diseases out of healthy leaves,with the ability to distinguish plant leaves from their surroundings.

Keywords: Conventional Neural Networks;

Disease Classification;Deep Learning