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CVPR
2005
IEEE
16 years 1 months ago
Object Class Recognition Using Multiple Layer Boosting with Heterogeneous Features
We combine local texture features (PCA-SIFT), global features (shape context), and spatial features within a single multi-layer AdaBoost model of object class recognition. The fir...
Wei Zhang 0002, Bing Yu, Gregory J. Zelinsky, Dimi...
INFOCOM
2007
IEEE
15 years 6 months ago
Randomized k-Coverage Algorithms For Dense Sensor Networks
— We propose new algorithms to achieve k-coverage in dense sensor networks. In such networks, covering sensor locations approximates covering the whole area. However, it has been...
Mohamed Hefeeda, M. Bagheri
BMCBI
2008
114views more  BMCBI 2008»
14 years 12 months ago
WSPMaker: a web tool for calculating selection pressure in proteins and domains using window-sliding
Background: In the study of adaptive evolution, it is important to detect the protein coding sites where natural selection is acting. In general, the ratio of the rate of non-syno...
Yong Seok Lee, Tae-Hyung Kim, Tae-Wook Kang, Won-H...
WSOM
2009
Springer
15 years 6 months ago
Incremental Figure-Ground Segmentation Using Localized Adaptive Metrics in LVQ
Vector quantization methods are confronted with a model selection problem, namely the number of prototypical feature representatives to model each class. In this paper we present a...
Alexander Denecke, Heiko Wersing, Jochen J. Steil,...
ICVS
2009
Springer
15 years 6 months ago
Using Local Symmetry for Landmark Selection
Abstract. Most visual Simultaneous Localization And Mapping (SLAM) methods use interest points as landmarks in their maps of the environment. Often the interest points are detected...
Gert Kootstra, Sjoerd de Jong, Lambert Schomaker