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» Object Detection using Background Context
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ICRA
2010
IEEE
164views Robotics» more  ICRA 2010»
13 years 6 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
13 years 11 months ago
Stratified Learning of Local Anatomical Context for Lung Nodules in CT Images
The automatic detection of lung nodules attached to other pulmonary structures is a useful yet challenging task in lung CAD systems. In this paper, we propose a stratified statist...
Dijia Wu, Le Lu, Jinbo Bi, Yoshihisa Shinagawa, Ki...
ICIP
2009
IEEE
14 years 8 months ago
Learning Contextual Rules For Priming Object Categories In Images
In this paper we introduce and exploit the concept of contextual rules in the field of object detection. These rules are defined as associations between different object likelihoo...
EUSAI
2007
Springer
14 years 1 months ago
Context-Sensitive Microlearning of Foreign Language Vocabulary on a Mobile Device
Abstract. We explore the use of ubiquitous sensing in the home for contextsensitive microlearning. To assess how users would respond to frequent and brief learning interactions tie...
Jennifer Beaudin, Stephen S. Intille, Emmanuel Mun...
ICCV
2007
IEEE
14 years 9 months ago
Object Localisation Using Generative Probability Model for Spatial Constellation and Local Image Features
In this paper we apply state-of-the-art approach to object detection and localisation by incorporating local descriptors and their spatial configuration into a generative probabil...
Joni-Kristian Kamarainen, Miroslav Hamouz, Josef K...