Abstract
The representation layer, hidden layer and output layer neuron models of quantum convolution neural network were designed. Modified linear activation function Relu was used as the activation function, and the quantum rotation angle and neural connection weight were optimized by training error function. The simulation results of eight kinds of micro parts show that the recognition accuracy of quantum convolution neural network algorithm is higher, the time consumption is less and the recognition effect is better than other algorithms.
Publication Date
6-28-2021
First Page
120
Last Page
125
DOI
10.13652/j.issn.1003-5788.2021.06.020
Recommended Citation
Rui, HE and Ze-qing, DING
(2021)
"Recognition of micro parts based on quantum convolution neural network algorithm,"
Food and Machinery: Vol. 37:
Iss.
6, Article 20.
DOI: 10.13652/j.issn.1003-5788.2021.06.020
Available at:
https://www.ifoodmm.cn/journal/vol37/iss6/20
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