In this paper we discuss landmark based absolute localization of tiny autonomous mobile robots in a known environment. Landmark features are naturally occurring as it is not allow...
This paper deals with a recently proposed nonparametric approach to camera calibration, which is applicable to any type of sensor design. Currently, no relative quantitative perfo...
How an internal observer, that is not given any a priori knowledge or interpretation of what its sensors receives, learn to imitate seems a formidable issue from a viewpoint of a c...
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
Le Song, Sajid M. Siddiqi, Geoffrey J. Gordon, Ale...
This paper presents an implemented computational model of word acquisition which learns directly from raw multimodal sensory input. Set in an information theoretic framework, the ...