Clustering through SOM Consistency

Reference:

Nicolau Gonçalves and Ricardo Vigário. Clustering through som consistency. In Aurélio Campilho and Mohamed Kamel, editors, Proceedings of Image Analysis and Recognition, volume 7324 of Lecture Notes in Computer Science, pages 61–68, Aveiro, Portugal, 2012. Springer Berlin / Heidelberg.

Abstract:

Clustering is a classical tool in image analysis, with wide applications. Yet, most of its algorithmic solutions include a considerable amount of stochasticity, e . g . due to different initialisations. Here, we introduce a clustering method rooted on self organizing maps, that exploits the maps' intrinsic variability, to produce reliable clustering. Although only a subset of the data is consistently clustered, we show that this set is trustworthy, and can be used for posterior classification.

Suggested BibTeX entry:

@inproceedings{Goncalves2012ICIAR,
    address = {Aveiro, Portugal},
    author = {Gonçalves, Nicolau and Vigário, Ricardo},
    booktitle = {Proceedings of Image Analysis and Recognition},
    editor = {Aurélio Campilho and Mohamed Kamel},
    language = {eng},
    pages = {61-68},
    publisher = {Springer Berlin / Heidelberg},
    series = {Lecture Notes in Computer Science},
    title = {Clustering through SOM Consistency},
    volume = {7324},
    year = {2012},
}