Fuzzy Model estimation

Brief Description

Estimate feature fuzzy model parameters using 2 vector data (ground truth samples and wrong samples).

Tags

Feature Extraction

Long Description

Estimate feature fuzzy model parameters using 2 vector data (ground truth samples and wrong samples).

Parameters

Input Positive Vector Data (psin): Ground truth vector data for positive samples
Input Negative Vector Data (nsin): Ground truth vector data for negative samples
Belief Support (belsup): Dempster Shafer study hypothesis to compute belief
Plausibility Support (plasup): Dempster Shafer study hypothesis to compute plausibility
Criterion (cri): Dempster Shafer criterion (by default (belief+plausibility)/2)
Weighting (wgt): Coefficient between 0 and 1 to promote undetection or false detections (default 0.5)
initialization model (initmod): Initialization model (xml file) to be used. If the xml initialization model is set, the descriptor list is not used (specified using the option -desclist)
Descriptor list (desclist): List of the descriptors to be used in the model (must be specified to perform an automatic initialization)
Maximum number of iterations (maxnbit): Maximum number of optimizer iteration (default 200)
Optimizer Observer (optobs): Activate the optimizer observer
Output filename (out): Output model file name (xml file) contains the optimal model to perform information fusion.
Load otb application from xml file (inxml): Load otb application from xml file
Save otb application to xml file (outxml): Save otb application to xml file

Limitations

None.

Authors

OTB-Team