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...

Descripción completa

Detalles Bibliográficos
Autores principales: Hernández-Rabadán, Deny Lizbeth, Ramos-Quintana, Fernando, Guerrero Juk, Julian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4236890/
https://www.ncbi.nlm.nih.gov/pubmed/25538948
http://dx.doi.org/10.1155/2014/214674

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4236890/
https://www.ncbi.nlm.nih.gov/pubmed/25538948
http://dx.doi.org/10.1155/2014/214674

Ejemplares similares