DocumentCode
3462197
Title
Machine parts classification based on a digital neural network
Author
Ouslim, M. ; Curtis, K.M.
Author_Institution
Dept. of Electr. & Electron. Eng., Nottingham Univ., UK
Volume
2
fYear
1996
fDate
13-16 Oct 1996
Firstpage
643
Abstract
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
Keywords
image classification; learning (artificial intelligence); neural nets; RAM neuron; controlling parameters; data analysis; digital neural network; image processing; learning algorithm; machine parts classification; pRAM; probabilistic version; reinforcement learning; Data analysis; Image processing; Image resolution; Learning; Neural networks; Neurons; Phase change random access memory; Random access memory; Read-write memory; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronics, Circuits, and Systems, 1996. ICECS '96., Proceedings of the Third IEEE International Conference on
Conference_Location
Rodos
Print_ISBN
0-7803-3650-X
Type
conf
DOI
10.1109/ICECS.1996.584444
Filename
584444
Link To Document