Re-occurs among tags (visualisation, rendering, viewer, classification, ...)|ToDo: Clear up relation between Classification, Clustering, and Prediction and recognition (also in main EDAM)



Multicut workflow for large connectomics data. Using luigi for pipelining and caching processing steps. Most of the computations are done out-of-core using hdf5 as backend and implementations from nifty

Spine classification based on kernel density estimation


We propose to use a kernel density estimation (KDE) based approach for classification. This non-parametric approach intrinsically provides the likelihood of membership for each class in a principled manner. The implementation was used in Ghani2016. Any papers using this code should cite Ghani2016 accordingly. The software has been tested under Matlab R2013b.


Sample Data: Annotated two-photon images of dendritic spines