Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
Joni Pajarinen, Jaakko Peltonen, Ari Hottinen, Mik...
This paper examines the problem of moving object detection. More precisely, it addresses the difficult scenarios where background scene textures in the video might change over tim...
The varying object appearance and unlabeled data from new frames are always the challenging problem in object tracking. Recently machine learning methods are widely applied to tra...
This work considers the mini-slot scheduling problem in IEEE 802.16d wireless mesh networks (WMNs). An efficient mini-slot scheduling needs to take into account the transmission o...
We recently proposed a method for HMM adaptation to noisy environments called Linear Spline Interpolation (LSI). LSI uses linear spline regression to model the relationship betwee...