Identify the category of foilar disease
Author(s):
Pratiksha Wable, Paritosh Jain, Pankaj Chandre
Keywords:
CNN, Machine learning, keras, Tensorflow
Abstract
Accurate identification and early diagnosis of apple tree leaf disease can control the spread of infection, to reduce use of chemical fertilizers and pesticides, to improve the quality of apples and maintain the healthy development of apples. First, collect the images of leaves with or without disease from Kaggle, and it contains two common apple tree leaf diseases and healthy leaves. The common leaf diseases are scab, multiple diseases and Rust. We build our model using convolution neural network. The proposed network achieves overall accuracy of 96% in identifying the apple tree leaf disease.
Article Details
Unique Paper ID: 155494

Publication Volume & Issue: Volume 9, Issue 1

Page(s): 1269 - 1272
Article Preview & Download


Share This Article

Join our RMS

Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Call For Paper

Volume 11 Issue 1

Last Date for paper submitting for Latest Issue is 25 June 2024

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews