|
[1]
|
Zhang Jingcheng, Yuan Lin, Wang Jihua, et al. Research progress of crop diseases and pests monitoring based on remote sensing[J]. Transactions of the Chinese Society of Agricultural Engineering, 2012, 28(20):1-11. (in Chinese) |
|
[2]
|
Qiao Hongbo, Zhou Yinlin, Bai Youlu, et al. The primary research of detecting wheat powdery mildew using in-field and low altitude remote sensing[J]. Acta Phytophylacica Sinica, 2006, 33(4):341-344. (in Chinese) |
|
[3]
|
Yuan Lin, Zhang Jingcheng, Zhao Jinling, et al. Differentiation of yellow rust and powdery mildew in winter wheat and retrieving of disease severity based on leaf level spectral analysis[J]. Spectroscopy and Spectral Analysis, 2013, 33(6):1608-1614. (in Chinese) |
|
[4]
|
Zhang Jingcheng, Pu Ruiliang, Wang Jihua, et al. Detecting powdery mildew of winter wheat using leaf level hyperspectral measurements[J]. Computers Electronics in Agriculture, 2012, 85(1):13-23. |
|
[5]
|
Liang Dong, Liu Na, Zhang Dongyan, et al. Discrimination of powdery mildew and yellow rust of winter wheat using high-resolution hyperspectra and imageries[J]. Infrared and Laser Engineering, 2017, 46(1):0138004. (in Chinese) |
|
[6]
|
Newton A C, Hackett C A, Lowe R, et al. Relationship between canopy reflectance and yield loss due to disease in barley[J]. Annals of Applied Biology, 2015, 145(1):95-106. |
|
[7]
|
Mahlein A K, Rumpf T, Welke P, et al. Development of spectral indices for detecting and identifying plant diseases[J]. Remote Sensing of Environment, 2013, 1(128):21-30. |
|
[8]
|
Huang Linsheng, Zhang Dongyan, Liang Dong, et al. Continuous wavelet analysis for diagnosing stress characteristics of leaf powdery mildew.[J]. International Journal of Agriculture Biology, 2013, 15(1):34-40. |
|
[9]
|
Liang Dong, Yang Qinying, Huang Wenjiang, et al. Estimation of leaf area index based on wavelet transform and support vector machine regression in winter wheat[J]. Infrared and Laser Engineering, 2015, 44(1):335-340. (in Chinese) |
|
[10]
|
Liang Liang, Yang Minhua, Zhang Lianpeng, et al. Chlorophyll content inversion with hyperspectral technology for wheat canopy based on support vector regression algorithm[J]. Transactions of the Chinese Society of Agricultural Engineering, 2012, 28(20):162-171. (in Chinese) |
|
[11]
|
Ding Shifei, Qi Bingjuan, Tan Hongyan. An overview on theory and algorithm of support vector machines[J]. Journal of University of Electronic Science and Technology of China, 2011, 40(1):2-10. (in Chinese) |
|
[12]
|
Zhang Dongyan, Zhang Jingcheng, Zhu Dazhou, et al. Investigation of the hyperspectral image characteristics of wheat leaves under different stress[J]. Spectroscopy and Spectral Analysis, 2011, 31(4):1101-1105. (in Chinese) |
|
[13]
|
Huang Wenjiang, Guan Qingsong, Luo Juhua, et al. New optimized spectral indices for identifying and monitoring winter wheat diseases[J]. IEEE Journal of Selected Topics in Applied Earth Observations Remote Sensing, 2014, 7(6):2516-2524. |
|
[14]
|
Kononenko I. Estimating attributes:analysis and extensions of RELIEF[C]//European Conference on Machine Learning on Machine Learning, 1994:171-182. |
|
[15]
|
Zhang Difei, Zhang Jinsuo, Yao Keming, et al. Infrared ship-target recognition based on SVM classification[J]. Infrared and Laser Engineering, 2016, 45(1):0104004. (in Chinese) |
|
[16]
|
Liang Dong, Xie Qiaoyun, Huang Wenjiang, et al. Using least squares support vector machines to estimate time series leaf area index[J]. Infrared and Laser Engineering, 2014, 43(1):243-248. (in Chinese) |
点击查看大图
下载:
