A Survey of Existing Leaf Disease Techniques using Artificial Neural Network

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2018 by IJCTT Journal
Volume-59 Number-1
Year of Publication : 2018
Authors : RakshitKhajuria, Dr.Sunanda, Mr.Siddharth Singh
  10.14445/22312803/IJCTT-V59P109

MLA

RakshitKhajuria, Dr.Sunanda, Mr.Siddharth Singh "A Survey of Existing Leaf Disease Techniques using Artificial Neural Network". International Journal of Computer Trends and Technology (IJCTT) V59(1):52-62, May 2018. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract
Agriculture productivity is something on which Indian economy heavily depends. Major portion of India depends on agriculture. But due to diseases in leaves there is a great loss to farmers. In earlier times disease detection in plants was carried out by naked eyes observation method but it is not very efficient at medium to large scale. 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, Principle Component Analysis (PCA), Support Vector Machines