Evolution of Approximate Functions for Image Thresholding
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F21%3APU147243" target="_blank" >RIV/00216305:26230/21:PU147243 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9659876" target="_blank" >https://ieeexplore.ieee.org/document/9659876</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SSCI50451.2021.9659876" target="_blank" >10.1109/SSCI50451.2021.9659876</a>
Alternative languages
Result language
angličtina
Original language name
Evolution of Approximate Functions for Image Thresholding
Original language description
This paper investigates the utilisation of approximate addition and multiplication for designing image thresholding functions. Cartesian Genetic Programming is applied for the evolutionary design of circuits using various implementations of the approximate operations. The results are presented for various experimental setups and compared with the case when only exact addition and multiplication is considered. It will be shown that for some range of error metrics of the approximate operations the evolution provides solutions that are better than those provided by the exact operations. Moreover, the utilisation of approximate components allows reducing the implementation area of the resulting functions.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA19-10137S" target="_blank" >GA19-10137S: Designing and exploiting libraries of approximate circuits</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
IEEE Symposium Series on Computational Intelligence (IEEE SSCI)
ISBN
978-1-7281-9048-8
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
1-6
Publisher name
IEEE Computer Society
Place of publication
Los Alamos
Event location
Orlando
Event date
Dec 4, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000824464300057