A data-fusion approach to partially supervised classification

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 2, Issue , 2001, Pages 858-860

  Prieto, Diego Fernàndez ^a   Arino, Olivier ^a  

^a ESA ESRIN   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE ANALYSIS; MARKOV PROCESSES; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; PROBABILITY; RADIAL BASIS FUNCTION NETWORKS; SENSOR DATA FUSION; STATISTICAL METHODS;

MARKOV RANDOM FIELD; PARTIALLY SUPERVISED CLASSIFICATION;

REMOTE SENSING;

EID: 0035573615     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. Partially supervised classification using weighted unsupervised clustering
2. A technique for the selection of kernel-function parameters in RBF neural networks for classification of remote-sensing images
3. Automatic analysis of the difference image for unsupervised change detection
4. Consensus theoretic classification methods
5. Maximum likelihood from incomplete data via the EM algorithm