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Title: Classification of complex two-dimensional images in a parallel distributed processing architecture
Author: Simpson, Robert Gilmour
Awarding Body: University of Plymouth
Current Institution: University of Plymouth
Date of Award: 1992
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Neural network analysis is proposed and evaluated as a method of analysis of marine biological data, specifically images of plankton specimens. The quantification of the various plankton species is of great scientific importance, from modelling global climatic change to predicting the economic effects of toxic red tides. A preliminary evaluation of the neural network technique is made by the development of a back-propagation system that successfully learns to distinguish between two co-occurring morphologically similar species from the North Atlantic Ocean, namely Ceratium arcticum and C. longipes. Various techniques are developed to handle the indeterminately labelled source data, pre-process the images and successfully train the networks. An analysis of the network solutions is made, and some consideration given to how the system might be extended.
Supervisor: Not available Sponsor: Plymouth Marine Laboratory
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Parallel distributed processing Pattern recognition systems Pattern perception Image processing Computer engineering Bionics