Leaf Disease Detection Using Artificial Neural Network
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International Journal of Computer Trends and Technology (IJCTT) |  |
| © 2019 by IJCTT Journal | ||
| Volume-67 Issue-8 |
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| Year of Publication : 2019 | ||
| Authors : Rakshit Khajuria , Himani khajuria | ||
| DOI : 10.14445/22312803/IJCTT-V67I8P108 |
MLA Style:Rakshit Khajuria , Himani khajuria"Leaf Disease Detection Using Artificial Neural Network" International Journal of Computer Trends and Technology 67.8 (2019):43-50.
APA Style Rakshit Khajuria , Himani khajuria.Leaf Disease Detection Using Artificial Neural NetworkInternational Journal of Computer Trends and Technology, 67(8),43-50.
Abstract
Most of Indian population depends on agriculture productivity. Major population of India depends on agriculture. Many diseases in leaves like fungal, bacteria and viruses may cost great loss to farmers. Disease in leaf destroys the quality of leaf. There are many types of leaf disease but we worked on leaf spot disease by using Artificial Neural Network. Automatic detection techniques can be used for disease detection in plants is efficient and time saving and accuracy. The automation of plant disease identification has gained attention in last few years. So, with the improvement in ANN, its families and Machine learning techniques there is a significant scope of improvement in the pre-existing methodologies for leaf disease detection, segmentation and identification. With the help of modern sensors and imaging techniques the efficiency and accuracy of ANN model have significantly improved, as we know that the process is highly dependent on qualityof data sets and the algorithm we use to process these datasets. This study focuses on various implementations of these ANN’s and their benefits such that they deal out optimal or near optimal solutions.
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Keywords
Artificial neural network, Plant pathology, K-mean , Accuracy, Classification