Name
Abstract | ||
|---|---|---|
In developing computer vision systems for analyzing chromosome images, a central task is the classification of the 46 chromosomes into 24 groups. A combination of multilayer-perceptrons for classifying isolated chromosomes is described. It is demonstrated that these perform as well as, or significantly better than, a well-developed statistical classifier. A method is suggested for using a competitive network to take advantage of constraints on the assignment of chromosomes to groups as a means of improving the classification rate |
Year | DOI | Venue |
|---|---|---|
1993 | 10.1109/ICNN.1993.298734 | San Francisco, CA |
Keywords | Field | DocType |
biological techniques and instruments,computer vision,feedforward neural nets,image recognition,chromosome images,classification,competitive network,computer vision systems,multilayer-perceptrons,neural networks,multilayer perceptron,microscopy,cancer,image analysis,data mining,artificial neural networks,neural network | Computer science,Statistical classifier,Artificial intelligence,Artificial neural network,Classification rate,Machine learning | Conference |
Citations | PageRank | References |
3 | 0.42 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Errington, P.A. | 1 | 3 | 0.42 |
| Jim Graham | 2 | 200 | 132.51 |