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» The Dark Side of Object Learning: Learning Objects
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ISVC
2010
Springer
15 years 2 months ago
Symmetry Enhanced Adaboost
This paper describes a method to minimize the immense training time of the conventional Adaboost learning algorithm in object detection by reducing the sampling area. A new algorit...
Florian Baumann, Katharina Ernst, Arne Ehlers, Bod...
IJCV
2008
226views more  IJCV 2008»
15 years 4 months ago
LabelMe: A Database and Web-Based Tool for Image Annotation
We seek to build a large collection of images with ground truth labels to be used for object detection and recognition research. Such data is useful for supervised learning and qu...
Bryan C. Russell, Antonio Torralba, Kevin P. Murph...
TNN
2008
88views more  TNN 2008»
15 years 4 months ago
A Fault-Tolerant Regularizer for RBF Networks
In classical training methods for node open fault, we need to consider many potential faulty networks. When the multinode fault situation is considered, the space of potential faul...
Chi-Sing Leung, J. P. F. Sum
CIARP
2007
Springer
15 years 10 months ago
Learning in Computer Vision: Some Thoughts
Abstract. It is argued that the ability to generalise is the most important characteristic of learning and that generalisation may be achieved only if pattern recognition systems l...
Maria Petrou
PRICAI
2004
Springer
15 years 9 months ago
Covisibility-Based Map Learning Method for Mobile Robots
In previous work, we proposed a unique landmark-based map learning method for mobile robots based on the “co-visibility” information i.e., very coarse qualitative information o...
Takehisa Yairi