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» Tackling Large State Spaces in Performance Modelling
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CVPR
2009
IEEE
15 years 4 months ago
Efficient Representation of Local Geometry for Large Scale Object Retrieval
State of the art methods for image and object re- trieval exploit both appearance (via visual words) and local geometry (spatial extent, relative pose). In large scale problems,...
Michal Perdoch (Czech Technical University), Ondre...
CVPR
2008
IEEE
14 years 11 months ago
Lost in quantization: Improving particular object retrieval in large scale image databases
The state of the art in visual object retrieval from large databases is achieved by systems that are inspired by text retrieval. A key component of these approaches is that local ...
James Philbin, Ondrej Chum, Michael Isard, Josef S...
PAMI
2008
156views more  PAMI 2008»
13 years 8 months ago
Tied Factor Analysis for Face Recognition across Large Pose Differences
Face recognition algorithms perform very unreliably when the pose of the probe face is different from the gallery face: typical feature vectors vary more with pose than with identi...
Simon J. D. Prince, James H. Elder, Jonathan Warre...
WMPI
2004
ACM
14 years 2 months ago
An analytical model for software-only main memory compression
Abstract. Many applications with large data spaces that cannot run on a typical workstation (due to page faults) call for techniques to expand the effective memory size. One such t...
Irina Chihaia, Thomas R. Gross
ECWEB
2009
Springer
112views ECommerce» more  ECWEB 2009»
14 years 3 months ago
Towards Privacy Compliant and Anytime Recommender Systems
Abstract. Recommendation technologies have traditionally been used in domains such as E-commerce and Web navigation to recommend resources to customers so as to help them to get th...
Armelle Brun, Anne Boyer