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ALT
2003
Springer
14 years 12 days ago
Can Learning in the Limit Be Done Efficiently?
Abstract. Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to pot...
Thomas Zeugmann
CDC
2008
IEEE
120views Control Systems» more  CDC 2008»
13 years 10 months ago
Left invertibility of discrete systems with finite inputs and quantized output
Abstract-- The aim of this paper is to address left invertibility for dynamical systems with inputs and outputs in discrete sets. We study systems that evolve in discrete time with...
Nevio Dubbini, Benedetto Piccoli, Antonio Bicchi
ICB
2007
Springer
183views Biometrics» more  ICB 2007»
13 years 10 months ago
Factorial Hidden Markov Models for Gait Recognition
Gait recognition is an effective approach for human identification at a distance. During the last decade, the theory of hidden Markov models (HMMs) has been used successfully in th...
Changhong Chen, Jimin Liang, Haihong Hu, Licheng J...
CIMAGING
2010
133views Hardware» more  CIMAGING 2010»
13 years 10 months ago
Motion blur removal in nonlinear sensors
We address the problem of motion blur removal from an image sequence that was acquired by a sensor with nonlinear response. Motion blur removal in purely linear settings has been ...
Tomer Faktor, Tomer Michaeli, Yonina C. Eldar
ICVGIP
2008
13 years 10 months ago
Monocular Depth by Nonlinear Diffusion
Following the phenomenological approach of gestaltists, sparse monocular depth cues such as T- and X-junctions and the local convexity are crucial to identify the shape and depth ...
Jean-Michel Morel, Philippe Salembier