Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
An introduction to variable and feature selection
The Journal of Machine Learning Research
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Identification of citrus disease using color texture features and discriminant analysis
Computers and Electronics in Agriculture
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Automatic detection of skin defects in citrus fruits using a multivariate image analysis approach
Computers and Electronics in Agriculture
Review: A review of advanced techniques for detecting plant diseases
Computers and Electronics in Agriculture
Advanced Data Mining Techniques
Advanced Data Mining Techniques
Neural network prediction of ascorbic acid degradation in green asparagus during thermal treatments
Expert Systems with Applications: An International Journal
WEKA---Experiences with a Java Open-Source Project
The Journal of Machine Learning Research
Data Mining: Practical Machine Learning Tools and Techniques
Data Mining: Practical Machine Learning Tools and Techniques
Expert Systems with Applications: An International Journal
Automatic classification of granite tiles through colour and texture features
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
Citrus exports to foreign markets are severely limited today by fruit diseases. Some of them, like citrus canker, black spot and scab, are quarantine for the markets. For this reason, it is important to perform strict controls before fruits are exported to avoid the inclusion of citrus affected by them. Nowadays, technical decisions are based on visual diagnosis of human experts, highly dependent on the degree of individual skills. This work presents a model capable of automatic recognize the quarantine diseases. It is based on the combination of a feature selection method and a classifier that has been trained on quarantine illness symptoms. Citrus samples with citrus canker, black spot, scab and other diseases were evaluated. Experimental work was performed on 212 samples of mandarins from a Nova cultivar. The proposed approach achieved a classification rate of quarantine/not-quarantine samples of over 83% for all classes, even when using a small subset (14) of all the available features (90). The results obtained show that the proposed method can be suitable for helping the task of citrus visual diagnosis, in particular, quarantine diseases recognition in fruits.