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Supervised learning with potentials for neural network-based object recognition

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2 Author(s)
Starzyk, J.A. ; Dept. of Electr. & Comput. Eng., Ohio Univ., Athens, OH, USA ; Sinkuo Chai

Supervised learning techniques are widely used in object recognition based on neural networks. Presenting class-labelled samples to the neural network and employing certain learning criteria accomplish the supervised learning process. In this research we present a learning algorithm which uses the potential function between cluster centers and samples as the learning criterion. A learning process using Euclidean distance as the criterion is also performed. Results from both methods are compared

Published in:

System Theory, 1994., Proceedings of the 26th Southeastern Symposium on

Date of Conference:

20-22 Mar 1994

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