Identification of wheat leaf diseases and their severity based on elliptical-maximum margin criterion metric learning

Author(s):  
Bao Wenxia ◽  
Zhao Jian ◽  
Hu Gensheng ◽  
Zhang Dongyan ◽  
Huang Linsheng ◽  
...  
2011 ◽  
Vol 36 (12) ◽  
pp. 1661-1673
Author(s):  
Jun GAO ◽  
Shi-Tong WANG ◽  
Xiao-Ming WANG

Author(s):  
Yujie Zheng ◽  
Xiaojun Wu ◽  
Dongjun Yu ◽  
Jingyu Yang ◽  
Weidong Wang ◽  
...  

2016 ◽  
Vol 23 (3) ◽  
pp. 1239-1250
Author(s):  
J. Tahmoresnezhad ◽  
S. Hashemi

2014 ◽  
Vol 526 ◽  
pp. 324-329
Author(s):  
Jie Yuan ◽  
Hai Bing Hu ◽  
Wei Yuan ◽  
Yang Jia ◽  
Yong Ming Zhang

Nowadays as camera is applied widely, image fire detection becomes much popular. Many researchers are committed to analyze the RGB color model or even gray images. Actually they have some disadvantages. So this paper will present a new model based on Maximum Margin Criterion, a feature extraction criterion. As it is maximizing the difference of between-class scatter matrices and within-class scatter matrices, it does not depend on the nonsingularity of the within-class scatter matrix. First we will introduce the main idea and then give a mathematical description to apply the model to fire detection, with the algorithm we can calculate the result we need. At last we will put them into practice, use a database to do some experiments to present the performance of this method.


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