The gabor filter response generator is run on the image and 1080 features are generated. One of the feature images is shown below.
The ROC curves is shown below for one of the folds of boosting for various stages.
Wednesday, November 26, 2008
GentleBoost Classifer on Membrane detection
The feature set is a bunch of Gabor of filter responses (nFeatures = 1080). The membrane dataset is /usr/sci/crcnsdata/CRCNS/Synapses/data/CellMembraneDetection/stom-002.png. The membrane markup is done in the stom-002_clahe_diff_thresh_concomp_thin_edit.png file. The membranes are marked as black and non membranes are marked white. The membrane is used as the positive example and the membrance is eroded and the remaining area is used as negative example. There is space between membranes and non-membrane area that is not considered during the training. The ground truth data looks like the following image.
The gabor filter response generator is run on the image and 1080 features are generated. One of the feature images is shown below.
The ROC curves is shown below for one of the folds of boosting for various stages.
The gabor filter response generator is run on the image and 1080 features are generated. One of the feature images is shown below.
The ROC curves is shown below for one of the folds of boosting for various stages.
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1 comment:
Wow... Those look like excellent results. I can't wait for the next meeting to talk with you about them.
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