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» MUSETTE: a framework for knowledge capture from experience
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SMC
2007
IEEE
102views Control Systems» more  SMC 2007»
15 years 4 months ago
An improved immune Q-learning algorithm
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
CVPR
2011
IEEE
14 years 5 months ago
Learning Temporally Consistent Rigidities
We present a novel probabilistic framework for rigid tracking and segmentation of shapes observed from multiple cameras. Most existing methods have focused on solving each of thes...
Jean-Sebastien Franco, Edmond Boyer
ROMAN
2007
IEEE
179views Robotics» more  ROMAN 2007»
15 years 4 months ago
Online Affect Detection and Adaptation in Robot Assisted Rehabilitation for Children with Autism
–This paper presents a novel affect-sensitive human-robot interaction framework for rehabilitation of children with autism spectrum disorder (ASD) where the robot can detect the ...
Changchun Liu, Karla Conn, Nilanjan Sarkar, Wendy ...
TDP
2010
140views more  TDP 2010»
14 years 4 months ago
Movement Data Anonymity through Generalization
In recent years, spatio-temporal and moving objects databases have gained considerable interest, due to the diffusion of mobile devices (e.g., mobile phones, RFID devices and GPS ...
Anna Monreale, Gennady L. Andrienko, Natalia V. An...
CVPR
2011
IEEE
14 years 1 months ago
Kernelized Structural SVM Learning for Supervised Object Segmentation
Object segmentation needs to be driven by top-down knowledge to produce semantically meaningful results. In this paper, we propose a supervised segmentation approach that tightly ...
Luca Bertelli, Tianli Yu, Diem Vu, Salih Gokturk