Spine classification based on kernel density estimation

Type
Author
M U Ghani
Execution Platform
Programming Language
Supported image dimension
Interaction Level
License/Openness
License
MIT
Description

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

has biological terms
Entry Curator
Last modified
08/16/2018 - 17:46