Hand Shape Recognition based on Hyper Column Model
Atsushi Shimada, Naoyuki Tsuruta, Rin-ichiro Taniguchi · Kyushu University Institutional Repository (QIR) (Kyushu University) · 2005
Abstract — In this paper, we propose a recognition method of hand shapes using Hyper-Column Model (HCM). HCM is a model to recognize images, and consists of Hierarchical Self-Organizing Maps (HSOM) and Neocognitron (NC). HCM complements disadvantages of HSOM and NC, and inherits advantages from them. There is a problem, however, that HCM does not suit general image recognition since its learning method is an unsupervised one with competitive learning which is used by Self-Organizing Map (SOM). Therefore, we extended HCM to a supervised learnable model with an associative memory of SOM. We have found that an ability of HCM with supervised learning is superior to the one with unsupervised learning. I.