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<https://khub.utp.edu.my/scholars/id/eprint/2255> <http://purl.org/dc/terms/title> "Distributed multi-feature recognition scheme for greyscale images"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://khub.utp.edu.my/scholars/id/eprint/2255> <http://purl.org/ontology/bibo/abstract> "Contemporary image recognition schemes either rely on single-feature recognition or focus on solving multi-feature recognition using complex computational approaches. Furthermore these approaches tend to be of tightly-coupled nature, thus not readily deployable within computational networks. Distributed Hierarchical Graph Neuron (DHGN) is a distributed single-cycle learning pattern recognition algorithm that can scale from coarse-grained to fine-grained networks and it has comparable accuracy to contemporary image recognition schemes. In this paper, we present an implementation of DHGN that works for multi-feature recognition of images. Our scheme is able to disseminate recognition of each feature within an image to a separate computational subnetwork. Thereby allowing a number of features being analysed simultaneously using a uniform recognition process. We have conducted tests on a collection of greyscale facial images. The results show that our approach produces high recognition accuracy through a simple distributed process. Furthermore, our approach implements single-cycle learning known as collaborative-comparison learning where new patterns are continuously stored using collaborative approach without affecting previously stored patterns. Our proposed scheme demonstrates higher classification accuracy in comparison with Back-Propagation Neural Network for multi-class images. © 2010 Springer Science+Business Media, LLC."^^<http://www.w3.org/2001/XMLSchema#string> .
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