ISSN:
0173-0835
Keywords:
Isoelectric focusing
;
Digital image processing
;
Neural networks
;
Self-organizing feature maps
;
Back-propagation
;
Pattern recognition
;
Chemistry
;
Biochemistry and Biotechnology
Source:
Wiley InterScience Backfile Collection 1832-2000
Topics:
Biology
,
Chemistry and Pharmacology
Notes:
In a recent study, isoelectric focusing patterns were classified with a neural network using the back-propagation algorithm [1]. In order to further study the classification process and to generalize the presentation of electrophoretic patterns, Kohonen's self-organizing feature maps [2] were applied in this study. Although these feature maps are very efficient in many pattern recognition tasks, our data proved to be too complex for classification with an unsupervised system. Therefore, a second supervised network on top of the feature map was necessary. As in [3], a feed-forward network trained by the back-propagation algorithm was used. The final system allows us to correctly classify 90% of all wheat varieties. Moreover, the system proved to be reliable, reasonable in training time and shows the same accuracy in different experimental setups.
Additional Material:
10 Ill.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1002/elps.11501601156
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