We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Mika et al. [3] introduce a non-linear formulation of Fisher's linear discriminant, based the now familiar "kernel trick", demonstrating state-of-the-art performanc...
In this paper we explore use of a new rate-distortion metric for optimizing real-time Internet video streaming with the transmission control protocol (TCP). The basic idea is to c...
We present a biologically inspired neural network model of visual orienting (using saccadic eye movements) in which targets are preferentially selected according to their reward va...
We consider a simple method to improve the adaptiveness and flexibility of bit-interleaved coded modulation (BICM) for various channel models. With state-of-the art adaptive transm...