Cart (Loading....) | Create Account
Close category search window
 

VLSI implementations of CNNs for image processing and vision tasks: single and multiple chip approaches

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

5 Author(s)
Anguita, M. ; Dept. de Electron. y Tecnologia de Computadores, Granada Univ., Spain ; Pelayo, F.J. ; Ros, E. ; Palomar, D.
more authors

Three alternative VLSI analog implementations of cellular neural networks (CNNs) are described and demonstrated with fabricated and tested chips, which have been devised to perform image processing and vision tasks: a programmable low-power CNN with embedded photosensors; a compact fixed-template CNN based on unipolar current-mode signals; and basic CMOS circuits to build an extended and biologically-inspired CNN model using spikes. The first two VLSI approaches are intended for focal-plane image processing applications. The third one allows, since its dynamics is defined by process-independent local ratios and its input/output can be efficiently multiplexed in time, the construction of very large multiple chip CNNs for more complex vision tasks

Published in:

Cellular Neural Networks and their Applications, 1996. CNNA-96. Proceedings., 1996 Fourth IEEE International Workshop on

Date of Conference:

24-26 Jun 1996

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.