By Topic

Machine parts classification based on a digital neural network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ouslim, M. ; Dept. of Electr. & Electron. Eng., Nottingham Univ., UK ; Curtis, K.M.

This paper describes the application of a digital neural network, based on the probabilistic version of the RAM neuron (pRAM), to image processing. The most important pRAM controlling parameters are discussed, along with the application of two types of learning algorithm, based on reinforcement learning and data analysis. The performance of the system is evaluated with respect to its classification of machine parts within a black and white image

Published in:

Electronics, Circuits, and Systems, 1996. ICECS '96., Proceedings of the Third IEEE International Conference on  (Volume:2 )

Date of Conference:

13-16 Oct 1996