{"pk":28985,"title":"A Convolutional Self-organizing Map for Visual Category Learning","subtitle":null,"abstract":"In this paper we present a novel neural network architecture that aims to combine the highly popular and successfulconvolutional neural network architecture with the learning mechanism of an unsupervised self-organizing map. The con-volutional self-organizing map (ConvSOM) is a hierarchical network consisting of several independent self-organizingmaps. It incorporates features associated with convolutional networks, such as weight sharing, spatial pooling, and hierar-chical abstraction, with the unsupervised, topographically organized self-organizing map. We will show that the resultingarchitecture performs poorly on the MNIST data set, but offers interesting avenues for further research.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Poster Presentations with Abstracts","is_remote":true,"remote_url":"https://escholarship.org/uc/item/62z7k1gj","frozenauthors":[{"first_name":"Chris","middle_name":"","last_name":"Gorman","name_suffix":"","institution":"University of Otago","department":""},{"first_name":"Lech","middle_name":"","last_name":"Szymanski","name_suffix":"","institution":"University of Otago","department":""},{"first_name":"Anthony","middle_name":"","last_name":"Robins","name_suffix":"","institution":"University of Otago","department":""},{"first_name":"Alistair","middle_name":"","last_name":"Knott","name_suffix":"","institution":"University of Otago","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2019-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/28985/galley/18856/download/"}]}