DocumentCode :
1574905
Title :
Research on classification of apple level based on neural network
Author :
Zhang Genshan ; Tian Hong ; Duan Liying ; Guan Huiming
Author_Institution :
Sch. of Literature & Media Transm., Shijiazhuang Univ., Shijiazhuang, China
Volume :
2
fYear :
2011
Firstpage :
1547
Lastpage :
1549
Abstract :
For the shortage of artificial methods in classification of apple level, a method of classification of apple level based on BP artificial neural networks is presented. Artificial neural network provides technical means for research on apple classification,because it can provide nonlinear mapping of the input vector and output vector with arbitrary dimension, and also can reach any nonlinear continuous system. The BP neural network model is established for the classification by taking feature parameters as input vectors and apple level as output vectors. The results has shown that the classification precision of model is very high, and which has good application in realizing automatic identification of apple level.
Keywords :
agricultural engineering; backpropagation; image classification; neural nets; vectors; BP artificial neural networks; apple level; classification; input vector; nonlinear mapping; output vector; Educational institutions; Yttrium; BP neural network; apple; classification; level;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cross Strait Quad-Regional Radio Science and Wireless Technology Conference (CSQRWC), 2011
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-9792-8
Type :
conf
DOI :
10.1109/CSQRWC.2011.6037265
Filename :
6037265
Link To Document :
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