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CVPR
2003
IEEE
16 years 5 months ago
Object Class Recognition by Unsupervised Scale-Invariant Learning
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...
Robert Fergus, Pietro Perona, Andrew Zisserman
113
Voted
ICPR
2004
IEEE
16 years 4 months ago
Optimally Regularised Kernel Fisher Discriminant Analysis
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...
Gavin C. Cawley, Kamel Saadi, Nicola L. C. Talbot
ICMCS
2006
IEEE
157views Multimedia» more  ICMCS 2006»
15 years 9 months ago
Using Rate-Distortion Metrics for Real-Time Internet Video Streaming with TCP
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...
Antonios Argyriou
142
Voted
ICANN
2010
Springer
15 years 4 months ago
Using Reinforcement Learning to Guide the Development of Self-organised Feature Maps for Visual Orienting
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...
Kevin Brohan, Kevin N. Gurney, Piotr Dudek
101
Voted
ETT
2006
102views Education» more  ETT 2006»
15 years 3 months ago
Bit-interleaved coded irregular modulation
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...
Frank Schreckenbach, Gerhard Bauch