Rice blast recognition based on principal component analysis and neural network

Author:

Xiao Maohua,Ma You,Feng Zhixiang,Deng Ziang,Hou Shishuang,Shu Lei,Lu ZhiXiong

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference29 articles.

1. Kumar, A., Mishra, A.K., Jain, A.K., 2016. In-silico identification of inhibitors for controlling rice blast. In: 2016 International Conference on Computing for Sustainable Global Development (INDIACom), pp. 1888–1892.

2. Joshi AA, Jadhav BD, 2016. Monitoring and controlling rice diseases using Image processing techniques. In: 2016 International Conference on Computing, Analytics and Security Trends (CAST), pp. 471–476.

3. Hyperspectral image analysis based on BoSW model for rice panicle blast grading;Huang;Comput. Electron. Agric.,2015

4. Screening and prevention of bacillus biocontrol against rice blast;Sha;Chinese J. Biol. Control.,2016

5. Detection of chlorotic cassava leaves using image processing and discriminant analysis;Abdullakasim;Thai Soc. Agric. Eng. J.,2015

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