Recognition method based on principal component analysis and back-propagation neural network

[in Chinese]; [in Chinese]; [in Chinese]

Journals >Infrared and Laser Engineering >Volume 34 >Issue 6 >Page 719 > Article

Infrared and Laser Engineering
Vol. 34, Issue 6, 719 (2005)

Recognition method based on principal component analysis and back-propagation neural network

[in Chinese]^*, [in Chinese], and [in Chinese]

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[in Chinese]

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[in Chinese], [in Chinese], [in Chinese]. Recognition method based on principal component analysis and back-propagation neural network[J]. Infrared and Laser Engineering, 2005, 34(6): 719 Copy Citation Text

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CLP Journals

[1] Zhou Jianmin, Fu Zhengqing, Li Peng, Yang Jun. Infrared nondestructive testing of cavity defects and PNN recognition and quantitative evaluation[J]. Infrared and Laser Engineering, 2015, 44(4): 1193

[2] Yin Yunhua, Li Huifang. RGB-D object recognition based on hybrid convolutional auto-encoder extreme learning machine[J]. Infrared and Laser Engineering, 2018, 47(2): 203008

[in Chinese], [in Chinese], [in Chinese]. Recognition method based on principal component analysis and back-propagation neural network[J]. Infrared and Laser Engineering, 2005, 34(6): 719

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