An Application of Convolutional Neural Networks for Automatic Inspection

Author

Calderon-Martinez, Jose A. ; Campoy-Cervera, Pascual

Author_Institution

Dept. of Electr. & Electron. Eng., Instituto Tecnologico de Aguascalientes

fYear

2006

fDate

7-9 June 2006

Firstpage

1

Lastpage

6

Abstract

Automatic inspection in today´s manufacturing is critical to be competitive. In this paper, experimental results from the application of digital filters for defects detection in paper pulp production are shown. These filters have been automatically generated by means of a convolutional neural architecture, that uses a modified back-propagation algorithm. The main subjects discussed are: convolutional top-down spiral architecture, a tool used to automatically generate digital filters, a simple but effective modification to the back-propagation algorithm for this application, and experimental results

Keywords

backpropagation; digital filters; inspection; neural nets; paper pulp; production engineering computing; artificial vision; automatic inspection; back-propagation algorithm; convolutional neural network; convolutional top-down spiral architecture; defect detection; digital filter; paper pulp production; Artificial neural networks; Digital filters; Graphics; Industrial electronics; Inspection; Manufacturing automation; Multi-layer neural network; Neural networks; Paper pulp; Production; Automatic inspection; artificial vision; convolutional neural networks; filters;

fLanguage

English

Publisher

ieee

Conference_Titel

Cybernetics and Intelligent Systems, 2006 IEEE Conference on

Conference_Location

Bangkok

Print_ISBN

1-4244-0023-6

Type

conf

DOI

10.1109/ICCIS.2006.252310

Filename

4017869