TY - GEN
T1 - The research of neural network study system in vehicle identification
AU - Li, Xiaoping
AU - Dong, Hongjian
AU - Lv, Xiaoxing
AU - Liu, Luyang
PY - 2010
Y1 - 2010
N2 - This dissertation also used BP network to recognize the characters of the vehicle plates. However, BP network has inherent defects and, by improving it with network learning method, this dissertation proved the possibility of an increased network learning efficiency, effectively solving the low-speed and local minimum problems of the neural network constringency. Furthermore, it introduced the variable differentiations of NN learning methods, greatly enhancing the performance of the whole system.
AB - This dissertation also used BP network to recognize the characters of the vehicle plates. However, BP network has inherent defects and, by improving it with network learning method, this dissertation proved the possibility of an increased network learning efficiency, effectively solving the low-speed and local minimum problems of the neural network constringency. Furthermore, it introduced the variable differentiations of NN learning methods, greatly enhancing the performance of the whole system.
KW - Bp network
KW - Neural network
KW - Vecial identification
KW - Vehicle plate
UR - http://www.scopus.com/inward/record.url?scp=77957784789&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:77957784789
SN - 9788988678183
T3 - NISS2010 - 4th International Conference on New Trends in Information Science and Service Science
SP - 355
EP - 359
BT - NISS2010 - 4th International Conference on New Trends in Information Science and Service Science
T2 - 4th International Conference on New Trends in Information Science and Service Science, NISS2010
Y2 - 11 May 2010 through 13 May 2010
ER -