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» Estimating Vision Parameters given Data with Covariances
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CVPR
2012
IEEE
11 years 9 months ago
Geodesic flow kernel for unsupervised domain adaptation
In real-world applications of visual recognition, many factors—such as pose, illumination, or image quality—can cause a significant mismatch between the source domain on whic...
Boqing Gong, Yuan Shi, Fei Sha, Kristen Grauman
IPMI
2005
Springer
14 years 6 days ago
Fundamental Limits in 3D Landmark Localization
This work analyses the accuracy of estimating the location of 3D landmarks and characteristic image structures. Based on nonlinear estimation theory we study the minimal stochastic...
Karl Rohr
ISD
1999
Springer
149views Database» more  ISD 1999»
13 years 11 months ago
Cost-Effective Determination of Biomass from Aerial Images
This paper describes an ongoing collaborative research program between the Computer Science and the Forestry and Wildlife Management Departments at the University of Massachusetts...
Howard J. Schultz, Dana Slaymaker, Chris Holmes, F...
ICCV
2007
IEEE
14 years 8 months ago
Spherical-Homoscedastic Shapes
Shape analysis requires invariance under translation, scale and rotation. Translation and scale invariance can be realized by normalizing shape vectors with respect to their mean ...
Onur C. Hamsici, Aleix M. Martínez
CORR
2010
Springer
210views Education» more  CORR 2010»
13 years 6 months ago
Exploiting Statistical Dependencies in Sparse Representations for Signal Recovery
Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in...
Tomer Faktor, Yonina C. Eldar, Michael Elad