Classification of chromosomes using higher-order neural networks

In this paper, the application of a higher-order neural network for the classification of human chromosomes is described. The neural network´s inputs are 30 dimensional feature space extracted from chromosome images and the outputs are 24 different chromosome classes. The neural network has been tested using both Copenhagen and Philadelphia human chromosome image databases. The performance of the proposed neural network classifier is superior to those classifiers reported before