In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...
We present a new approach to model visual scenes in image collections, based on local invariant features and probabilistic latent space models. Our formulation provides answers to...
Pedro Quelhas, Florent Monay, Jean-Marc Odobez, Da...
This paper presents a novel real-time palmprint recognition system for cooperative user applications. This system is the first one achieving noncontact capturing and recognizing pa...
In this paper, we propose a fully automatic dynamic scratchpad memory (SPM) management technique for instructions. Our technique loads required code segments into the SPM on deman...
Bernhard Egger, Chihun Kim, Choonki Jang, Yoonsung...