Logistic Disjunctive Normal Networks


Logistic disjunctive normal network (LDNN) is a novel classification scheme, which consists of one adaptive layer of feature detectors implemented by logistic sigmoid functions followed by two fixed layers of logical units that compute conjunctions and disjunctions, respectively.

Matlab Codes

The source code and precompiled binaries for different platforms are available here.

-If you want to compile the mex files use “compile.m” script available in the package.

-We integrated the kmeans function of the berkley vision group for clustering.

-”LDNN_train.m” is the main function for training the classifier and “LDNN_predict.m” is the main function for testing the classifier.

-You can use “demo.m” to run some examples.

If you use this package please cite the following:

Image Segmentation with Cascaded Hierarchical Models and Logistic Disjunctive Normal Networks M. Seyedhosseini, M. Sajjadi, and T. Tasdizen, ICCV 2013 [pdf,bibtex]


A journal version of the LDNN classifier is under preparation. October 4th 2013

Version 1.0 was released. October 2nd 2013


If you have any questions please email me or Mehdi Sajjadi.