Integrating SOMs and a Bayesian Classifier for Segmenting Diseased Plants in Uncontrolled Environments
This work presents a methodology that integrates a nonsupervised learning approach (self-organizing map (SOM)) and a supervised one (a Bayesian classifier) for segmenting diseased plants that grow in uncontrolled environments such as greenhouses, wherein the lack of control of illumination and prese...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/214674 |
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