Recognition of micro parts based on quantum convolution neural network algorithm
CSTR:
Author:
Affiliation:

(1. Yellow River Conservancy Technical College, Kaifeng, Henan 475004, China;2. Nanyang Technician College, Nanyang, Henan 473000, China)

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    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.

    Reference
    Related
    Cited by
Get Citation

何瑞,丁泽庆.基于量子卷积神经网络算法的微小零件识别[J].食品与机械英文版,2021,37(6):120-125.

Copy
Related Videos

Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:February 09,2021
  • Revised:
  • Adopted:
  • Online: February 15,2023
  • Published:
Article QR Code