DocumentCode
2682950
Title
Neuro-inspired learning of low-level image processing tasks for implementation based on nano-devices
Author
Brousse, Olivier ; Paindavoine, Michel ; Gamrat, Christian
Author_Institution
LEAD, Univ. Bourgogne, Dijon, France
fYear
2010
fDate
23-25 March 2010
Firstpage
1
Lastpage
4
Abstract
As nanoscale devices such as OG-CNTFETs are under studies and may be used in a near futur, we choose to investigate in wich application domain such components may be of the most interest. In this paper we present how neural networks can be used to implement functions on nano-scale components. This method has been tested in the image processing application field.
Keywords
image processing; learning (artificial intelligence); neural nets; OG-CNTFETs; low-level image processing tasks; nano-devices; neural networks; neuro-inspired learning; Embedded computing; Energy consumption; Image coding; Image edge detection; Image processing; Mobile computing; Nanoscale devices; Neural networks; Signal processing algorithms; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Design and Technology of Integrated Systems in Nanoscale Era (DTIS), 2010 5th International Conference on
Conference_Location
Hammamet
Print_ISBN
978-1-4244-6338-1
Type
conf
DOI
10.1109/DTIS.2010.5487553
Filename
5487553
Link To Document