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Classification of marine phytoplankton (dinoflagellates) using neural networks

Objective



This project is concerned with the assessment of utility of two artificial neural networks (back propagation of error and radial basis function) for the automatic categorization of marine dinoflagellates. Over 2.000 photomicrographs of dinoflagellates are being collected, validated by panels of experts and digitized into a computer. This validated data set will be used to make a comparative assessment of neural network algorithms with classical image processing techniques such as principle component analysis.

Work is also being undertaken on improving the robustness of artificial neural network algorithms to noise, clutter, and multiple specimens within images using connectionist techniques being developed by the cognitive psychology community and others. Additionally, a prototype computer-based training tool using the validated data set is being developed. This tool will be disseminated on a trial basis by satellite link to a number of sites in Europe and will be evaluated as a training aid to ecologists working in marine and coastal management.

Funding Scheme

CSC - Cost-sharing contracts

Coordinator

UNIVERSITY OF PLYMOUTH
Address
Drake Circus
Plymouth
United Kingdom

Participants (3)

INSTITUTO ESPANOL DE OCEANOGRAFIA
Spain
Address
1552,Apdo 1552, Subida A Radio Faro 50
36280 Vigo
NERC Centre of Coastal and Marine Sciences
United Kingdom
Address
Prospect Place West Hoe
PL1 3DH Plymouth
UNIVERSITY OF GENOVA
Italy
Address
13,Via All'opera Pia 13
16145 Genova