Data clustering is prevalent in almost all areas technology and science, from identifying documents that are similar to analyzing biological images. SALR particle clustering is a data clustering technique for locating the centers of partially overlapping objects or distributions.
SALR particle clustering can be applied to any problem where the center of overlapping objects or distributions needs to be found. This covers a broad range of fields, from unsupervised maching learning and data clustering to locating the centers of overlapping nuclei in biological images.
SALR particle clustering is written in Matlab. Setup is as simple as downloading the repository and running the included setup functions. The code is fully documented with several examples to get you started using it quickly.