2-D Object Recognition by Structured Neural Networks in a Pyramidal Architecture

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	Similar Articles Articles by V. Cantoni Articles by A. Petrosino

Fifth IEEE International Workshop on Computer Architectures for Machine Perception (CAMP'00)

Padova, Italy

September 11-September 13

ISBN: 0-7695-0740-9

	ASCII Text	x
	V. Cantoni, A. Petrosino, "2-D Object Recognition by Structured Neural Networks in a Pyramidal Architecture," Computer Architectures for Machine Perception, International Workshop on, pp. 81, Fifth IEEE International Workshop on Computer Architectures for Machine Perception (CAMP'00), 2000.

	BibTex	x
	@article{ 10.1109/CAMP.2000.875961, author = {V. Cantoni and A. Petrosino}, title = {2-D Object Recognition by Structured Neural Networks in a Pyramidal Architecture}, journal ={Computer Architectures for Machine Perception, International Workshop on}, volume = {0}, year = {2000}, isbn = {0-7695-0740-9}, pages = {81}, doi = {http://doi.ieeecomputersociety.org/10.1109/CAMP.2000.875961}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer Architectures for Machine Perception, International Workshop on TI - 2-D Object Recognition by Structured Neural Networks in a Pyramidal Architecture SN - 0-7695-0740-9 SP EP A1 - V. Cantoni, A1 - A. Petrosino, PY - 2000 KW - object recognition; object recognition; structured neural networks; pyramidal architecture; pattern recognition; hierarchical modular structure; SIMD machine; image correlation VL - 0 JA - Computer Architectures for Machine Perception, International Workshop on ER -

V. Cantoni, Dipt. di Inf. e Sistemistica, Pavia Univ., Italy

A. Petrosino, Dipt. di Inf. e Sistemistica, Pavia Univ., Italy

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CAMP.2000.875961

In the paper we propose an approach to the realization of models inspired to biological solutions for pattern recognition. The approach is based on a hierarchical modular structure capable to learn by examples and recognize objects in digital images. The adopted techniques are based on multiresolution image correlation and neural networks. Performance on two different data sets and experimental timings on a SIMD machine are also reported.

Index Terms:

object recognition; object recognition; structured neural networks; pyramidal architecture; pattern recognition; hierarchical modular structure; SIMD machine; image correlation

Citation:

V. Cantoni, A. Petrosino, "2-D Object Recognition by Structured Neural Networks in a Pyramidal Architecture," camp, pp.81, Fifth IEEE International Workshop on Computer Architectures for Machine Perception (CAMP'00), 2000

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