A Hybrid Combination of Multiple SVM Classifiers for Automatic Recognition of the Damages and Symptoms on Plant Leaves
Authors:
- 7 May 2016
- book chapter
- Published by Springer Nature in Lecture Notes in Computer Science
- p. 40-50
Abstract
No abstract availableKeywords
This publication has 10 references indexed in Scilit:
- Automatic Recognition of the Damages and Symptoms on Plant Leaves Using Parallel Combination of Two Classifiers2016
- Serial combination of two classifiers for automatic recognition of the damages and symptoms on plant leaves2015
- A survey of multiple classifier systems as hybrid systemsInformation Fusion, 2014
- “Diagnosis and classification of grape leaf diseases using neural networks”2013
- Image recognition of plant diseases based on backpropagation networks2012
- SVM and Haralick Features for Classification of High Resolution Satellite Images from Urban Areas2012
- Detection and Classification of Leaf Diseases using K-means-based Segmentation and Neural-networks-based ClassificationInformation Technology Journal, 2011
- A survey of cross-validation procedures for model selectionStatistics Surveys, 2010
- Image pattern classification for the identification of disease causing agents in plantsComputers and Electronics in Agriculture, 2009
- A comparison of methods for multiclass support vector machinesIEEE Transactions on Neural Networks, 2002