—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...
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...
–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 ...
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...
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 ...