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ICCV
2007
IEEE
14 years 11 months ago
Active Learning with Gaussian Processes for Object Categorization
Discriminative methods for visual object category recognition are typically non-probabilistic, predicting class labels but not directly providing an estimate of uncertainty. Gauss...
Ashish Kapoor, Kristen Grauman, Raquel Urtasun, Tr...
TIP
2010
155views more  TIP 2010»
13 years 8 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He
ICDM
2008
IEEE
109views Data Mining» more  ICDM 2008»
14 years 4 months ago
Learning by Propagability
In this paper, we present a novel feature extraction framework, called learning by propagability. The whole learning process is driven by the philosophy that the data labels and o...
Bingbing Ni, Shuicheng Yan, Ashraf A. Kassim, Loon...
CVPR
2012
IEEE
12 years 1 days ago
A learning based deformable template matching method for automatic rib centerline extraction and labeling in CT images
The automatic extraction and labeling of the rib centerlines is a useful yet challenging task in many clinical applications. In this paper, we propose a new approach integrating r...
Dijia Wu, David Liu, Zoltan Puskas, Chao Lu, Andre...
PERCOM
2004
ACM
14 years 9 months ago
Learning to Detect User Activity and Availability from a Variety of Sensor Data
Using a networked infrastructure of easily available sensors and context-processing components, we are developing applications for the support of workplace interactions. Notions o...
Dave Snowdon, Jean-Luc Meunier, Martin Mühlen...