Guessing an Unknown Class by Online Fast Attributes Learning and Transfer

Abstract

Towards building an intelligent robot, we have to create an autonomous mental development system that incrementally and speedily learns from humans, their environments, and the Internet. In this paper, we propose an ultrafast and online incremental attributes learning and transfer method using new SOINN; stand for Self-Organizing and Incremental Neural Network. We conducted a comparison experiment with previous methods. Based on these results, our proposed method can keep an equivalent recognition rate of an online method, and shorten the learning time and test time. And another advantage is to be able to use the Internet data, and be dened real valued attributes.