DocumentCode
1744971
Title
On the performance of CNNs for associative memories in robot vision systems
Author
Brucoli, Michele ; Cafagna, Donato ; Carnimeo, Leonavda
Author_Institution
Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari, Italy
Volume
3
fYear
2001
fDate
6-9 May 2001
Firstpage
341
Abstract
In this paper a DTCNN-based vision system for pattern recognition in an artificial vision architecture is illustrated. The bipolar images, segmented in a preprocessing stage, constitute the input to a cellular associative memory in the recognizing stage of the vision system. The performance of DTCNNs designed as associative memories is confirmed by means of examples of detection and recognition of tools handled by a robot in an assembly line
Keywords
cellular neural nets; content-addressable storage; image segmentation; industrial robots; pattern recognition; robot vision; assembly line; associative memory; bipolar image segmentation; discrete time cellular neural network; pattern recognition; robot vision system; tool detection; Associative memory; Belts; Cellular neural networks; Data preprocessing; Image processing; Image segmentation; Machine vision; Object detection; Robot vision systems; Robotic assembly;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2001. ISCAS 2001. The 2001 IEEE International Symposium on
Conference_Location
Sydney, NSW
Print_ISBN
0-7803-6685-9
Type
conf
DOI
10.1109/ISCAS.2001.921317
Filename
921317
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