Probabilistic neural network as chromosome classifier
This paper applies a probabilistic neural network (PNN) towards the classification of human chromosomes. The inputs to the network are thirty different features extracted from the chromosome image. The output is one of twenty-four different classes of chromosomes. The network has been tested on Cope...
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Published in | IEEE, PISCATAWAY, NJ, (USA). Vol. 1, pp. 935-937. 1993 Vol. 1; pp. 935 - 938 vol.1 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
1993
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Subjects | |
Online Access | Get full text |
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Summary: | This paper applies a probabilistic neural network (PNN) towards the classification of human chromosomes. The inputs to the network are thirty different features extracted from the chromosome image. The output is one of twenty-four different classes of chromosomes. The network has been tested on Copenhagen, Edinburgh and Philadelphia databases. The recognition rates achieved in this study are better than conventional methods and comparable to another neural network technique, that has been previously reported. |
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Bibliography: | SourceType-Books-1 ObjectType-Book-1 content type line 25 ObjectType-Conference-2 SourceType-Conference Papers & Proceedings-2 |
ISBN: | 0780314212 9780780314214 |
DOI: | 10.1109/IJCNN.1993.714064 |