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CVPR
2011
IEEE
15 years 2 months ago
What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms
In real-world applications, “what you saw” during training is often not “what you get” during deployment: the distribution and even the type and dimensionality of features...
Brian Kulis, Kate Saenko, Trevor Darrell
EVOW
2012
Springer
14 years 2 months ago
HyFlex: A Benchmark Framework for Cross-Domain Heuristic Search
This paper presents HyFlex, a software framework for the development of cross-domain search methodologies. The framework features a common software interface for dealing with diff...
Gabriela Ochoa, Matthew R. Hyde, Timothy Curtois, ...
ICIP
2001
IEEE
16 years 8 months ago
All-phase motion compensated prediction in the wavelet domain for high performance video coding
This paper presents a novel framework of motion compensated pre&ction(MCP) techniques in the wavelet domain for high performance video coding. Our analysis reveals fundamental...
Xin Li, Louis Kerofsky, Shawmin Lei
SEKE
2009
Springer
16 years 1 months ago
Bridging Semantic Gaps Between Stakeholders in the Production Automation Domain with Ontology Areas
Abstract—Stakeholders from several domains with local terminologies have to work together to develop and operate softwareintensive systems, like production automation systems. On...
Stefan Biffl, Wikan Danar Sunindyo, Thomas Moser
JMLR
2012
13 years 9 months ago
Domain Adaptation: A Small Sample Statistical Approach
We study the prevalent problem when a test distribution differs from the training distribution. We consider a setting where our training set consists of a small number of sample d...
Ruslan Salakhutdinov, Sham M. Kakade, Dean P. Fost...