Cellular neural networks for image processing tasks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F10%3AA1100YDG" target="_blank" >RIV/61988987:17310/10:A1100YDG - isvavai.cz</a>

Result on the web

—

DOI - Digital Object Identifier

—

Result language

angličtina

Original language name

Cellular neural networks for image processing tasks

Original language description

Cellular neural networks (CNNs) are similar to artificial neural networks (ANNs) in that they are composed of many distributed processing elements, called ?cells?, which are connected in a network. CNNs were designed to operate in a two-dimensional grid,where each processing element (cell) is connected to neighboring cells in the grid. CNNs have been shown to be an adept at image processing tasks. Specifically, CNN cells maintain a state which evolves through time due to differential equations dependent on the cell's inputs and feedback. This article introduces software for graphics processing units (GPUs) by abstracting the hardware as arrays of configurable CNNs cells. Introducing an efficient CNN-based abstraction of GPU computation should encourage the study of massively parallel computation using tools and methods of dynamic systems theory and abstract automata theory.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

IN - Informatics

OECD FORD branch

—

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2010

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Mendel 2010

ISBN

978-80-214-4120-0

ISSN

—

e-ISSN

—

Number of pages

6

Pages from-to

—

Publisher name

Brno Univerzity of Technology

Place of publication

Brno

Event location

Brno

Event date

Jun 23, 2010

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000288144100042