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» A Model Selection Approach for Local Learning
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CVPR
2010
IEEE
15 years 3 months ago
Latent Hierarchical Structural Learning for Object Detection
We present a latent hierarchical structural learning method for object detection. An object is represented by a mixture of hierarchical tree models where the nodes represent objec...
Leo Zhu, Yuanhao Chen, Antonio Torralba, Alan Yuil...
AAAI
2004
14 years 11 months ago
Rapid Object Recognition from Discriminative Regions of Interest
Object recognition and detection represent a relevant component in cognitive computer vision systems, such as in robot vision, intelligent video surveillance systems, or multi-mod...
Gerald Fritz, Christin Seifert, Lucas Paletta, Hor...
ICML
2007
IEEE
15 years 10 months ago
Learning a meta-level prior for feature relevance from multiple related tasks
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
BMCBI
2006
169views more  BMCBI 2006»
14 years 10 months ago
Machine learning techniques in disease forecasting: a case study on rice blast prediction
Background: Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their ...
Rakesh Kaundal, Amar S. Kapoor, Gajendra P. S. Rag...
ICRA
2010
IEEE
101views Robotics» more  ICRA 2010»
14 years 8 months ago
Searching for objects: Combining multiple cues to object locations using a maximum entropy model
— In this paper, we consider the problem of how background knowledge about usual object arrangements can be utilized by a mobile robot to more efficiently find an object in an ...
Dominik Joho, Wolfram Burgard