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DPHOTO
2010
360views Hardware» more  DPHOTO 2010»
13 years 9 months ago
Signal-dependent raw image denoising using sensor noise characterization via multiple acquisitions
Accurate noise level estimation is essential to assure good performance of noise reduction filters. Noise contaminating raw images is typically modeled as additive white and Gauss...
Angelo Bosco, Arcangelo Bruna, D. Giacalone, Sebas...
JAIR
2002
163views more  JAIR 2002»
13 years 7 months ago
Efficient Reinforcement Learning Using Recursive Least-Squares Methods
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
Xin Xu, Hangen He, Dewen Hu
CVPR
2006
IEEE
14 years 1 months ago
A Modular Approach to the Analysis and Evaluation of Particle Filters for Figure Tracking
This paper presents the first systematic empirical study of the particle filter (PF) algorithms for human figure tracking in video. Our analysis and evaluation follows a modula...
Ping Wang, James M. Rehg
TJS
2002
160views more  TJS 2002»
13 years 7 months ago
Adaptive Optimizing Compilers for the 21st Century
Historically, compilers have operated by applying a fixed set of optimizations in a predetermined order. We call such an ordered list of optimizations a compilation sequence. This...
Keith D. Cooper, Devika Subramanian, Linda Torczon
GECCO
2009
Springer
121views Optimization» more  GECCO 2009»
14 years 11 days ago
Using memetic algorithms to improve portfolio performance in static and dynamic trading scenarios
The Portfolio Optimization problem consists of the selection of a group of assets to a long-term fund in order to minimize the risk and maximize the return of the investment. This...
Claus de Castro Aranha, Hitoshi Iba