Abstract
A neural network trained by the genetic algorithms (GANN) is presented. Each neuron of the network forms a closed region in the input space. The closed regions which are formed by the neurons overlap each other, like STAR. Genetic algorithms are used to improve the classification performances of the magnetic resonance (MR) images with minimized number of neurons. GANN is examined comparatively with multilayer perceptron (MLP), and restricted coulomb energy (RCE). It is observed that GANN gives the best classification performance with less number of neurons after a short training time.
| Original language | English |
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| Pages (from-to) | 1391-1393 |
| Number of pages | 3 |
| Journal | Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings |
| Volume | 3 |
| Publication status | Published - 1997 |
| Event | Proceedings of the 1997 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Chicago, IL, USA Duration: 30 Oct 1997 → 2 Nov 1997 |