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125
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ICRA
2010
IEEE
164views Robotics» more  ICRA 2010»
14 years 11 months ago
Boundary detection based on supervised learning
— Detecting the boundaries of objects is a key step in separating foreground objects from the background, which is useful for robotics and computer vision applications, such as o...
Kiho Kwak, Daniel F. Huber, Jeongsook Chae, Takeo ...
CVPR
2010
IEEE
14 years 10 months ago
P-N learning: Bootstrapping binary classifiers by structural constraints
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
Zdenek Kalal, Jiri Matas, Krystian Mikolajczyk
CVPR
2012
IEEE
13 years 3 months ago
Teaching 3D geometry to deformable part models
Current object class recognition systems typically target 2D bounding box localization, encouraged by benchmark data sets, such as Pascal VOC. While this seems suitable for the de...
Bojan Pepik, Michael Stark, Peter V. Gehler, Bernt...
99
Voted
ISBI
2004
IEEE
16 years 1 months ago
Reconstruction of 2D Pet Data with Monte Carlo Generated Natural Pixels
Abstract-In discrete detector PET, natural pixels are image basis functions calculated from responses of detector pairs. By using reconstruction with natural pixels the discretizat...
Charles L. Byrne, Stefaan Vandenberghe, Edward J. ...
CPAIOR
2009
Springer
15 years 7 months ago
Modelling Search Strategies in Rules2CP
In this abstract, we present a rule-based modelling language for constraint programming, called Rules2CP [1], and a library PKML for modelling packing problems. Unlike other modell...
François Fages, Julien Martin