Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/4359
Title: Invariant pattern recognition with higher-order neural networks
Authors: He, Zhengquan.
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Issue Date: 1999
Abstract: Translation, rotation (in plane) and scale invariant pattern recognition is a high-order recognition problem encountered frequently in real-world applications. But neither traditional image process/pattern recognition algorithms nor artificial neural networks have yet provided satisfactory solutions for this problem after years of study. Recent research has shown that a higher order neural networks (HONNs) of order three with built-in invariances can effectively achieve invariant pattern recognition.
URI: http://hdl.handle.net/10356/4359
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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