Belciug, Smaranda and El-Darzi, Elia (2010) A partially connected neural network-based approach with application to breast cancer detection and recurrence. In: 5th IEEE International Conference on Intelligent Systems (IS 2010) proceedings. IEEE, pp. 191-196. ISBN 9781424451647
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Official URL: http://dx.doi.org/10.1109/IS.2010.5548358
The fully connected feed-forward neural networks are commonly used in almost all neural networks applications, since such architecture provides the best generalisation power. However, they need large computing resources and have low speed when they are applied to large databases. The aim of this paper is to assess the effectiveness of an alternative approach, based on a partially connected neural network, using four significantly different breast cancer datasets for comparison. Thus, reducing the computing resource consumption during the classification process, and increasing the speed as well, this simplified neural network type succeeded in obtaining very good accuracy in comparison with a fully connected neural network.
|Item Type:||Book Section|
|Research Community:||University of Westminster > Electronics and Computer Science, School of|
|Deposited On:||11 Nov 2010 10:42|
|Last Modified:||11 Nov 2010 10:42|
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