Artifacts using weka-dev version 3.9.5

Trainable Segmentation plugin for Fiji.

The MEKA project provides an open source implementation of methods for multi-label classification and evaluation. It is based on the WEKA Machine Learning Toolkit. Several benchmark methods are also included, as well as the pruned sets and classifier chains methods, other methods from the scientific literature, and a wrapper to the MULAN framework.

The mcib3d library is the core library for most of the mcib3d plugins.

The Labkit image segmentation tool for Fiji.

The implementation of the pixel classification algorithm, that is used the Labkit image segmentation plugin for Fiji.

T2-NIT component of TrakEM2 suite.

Contains modularized (jena-based) matchers that can be used to quickly assemble matching systems.

Mecj