Journal ArticleDOI
Rice diseases classification using feature selection and rule generation techniques
TLDR
A rule base classifier has been built that cover all the diseased rice plant images and provides superior result compare to traditional classifiers.About:
This article is published in Computers and Electronics in Agriculture.The article was published on 2013-01-01. It has received 165 citations till now. The article focuses on the topics: Feature extraction & Feature selection.read more
Citations
More filters
Journal ArticleDOI
A review on the main challenges in automatic plant disease identification based on visible range images
TL;DR: An analysis of the challenges faced by automatic plant disease identification using visible range images, emphasizing both the problems that they may cause and how they may have potentially affected the techniques proposed in the past.
Journal ArticleDOI
An in-field automatic wheat disease diagnosis system
TL;DR: Experimental results demonstrate that the proposed system outperforms conventional CNN architectures on recognition accuracy under the same amount of parameters, meanwhile maintaining accurate localization for corresponding disease areas.
Journal ArticleDOI
Current and future applications of statistical machine learning algorithms for agricultural machine vision systems
TL;DR: Current application of statistical machine learning techniques in machine vision systems, analyses each technique potential for specific application and represents an overview of instructive examples in different agricultural areas are surveyed.
Journal ArticleDOI
Plants Disease Identification and Classification Through Leaf Images: A Survey
TL;DR: The performance of state-of-the-art techniques are analyzed to identify those that seem to work well across several crops or crop categories and a set of acceptable techniques are discovered.
Journal ArticleDOI
Performance Analysis of Deep Learning CNN Models for Disease Detection in Plants using Image Segmentation
TL;DR: This research work investigates a potential solution to food security for the 7 billion people on earth by using segmented image data to train the convolutional neural network (CNN) models, and shows that the confidence of self-classification for S-CNN model improves significantly over F-CNN.
References
More filters
Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Book
C4.5: Programs for Machine Learning
TL;DR: A complete guide to the C4.5 system as implemented in C for the UNIX environment, which starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting.
Journal ArticleDOI
Bagging predictors
TL;DR: Tests on real and simulated data sets using classification and regression trees and subset selection in linear regression show that bagging can give substantial gains in accuracy.
Related Papers (5)
An image-processing based algorithm to automatically identify plant disease visual symptoms.
Anyela Camargo,Jeremy S. Smith +1 more