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» Learning Distance Functions for Image Retrieval
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ICPR
2008
IEEE
14 years 1 months ago
Semi-supervised learning by locally linear embedding in kernel space
Graph based semi-supervised learning methods (SSL) implicitly assume that the intrinsic geometry of the data points can be fully specified by an Euclidean distance based local ne...
Rujie Liu, Yuehong Wang, Takayuki Baba, Daiki Masu...
ICIP
2002
IEEE
14 years 9 months ago
Unsupervised image segmentation via Markov trees and complex wavelets
The goal in image segmentation is to label pixels in an image based on the properties of each pixel and its surrounding region. Recently Content-Based Image Retrieval (CBIR) has e...
Cián W. Shaffrey, Ian Jermyn, Nick G. Kings...
CVPR
2008
IEEE
14 years 9 months ago
Transfer learning for image classification with sparse prototype representations
To learn a new visual category from few examples, prior knowledge from unlabeled data as well as previous related categories may be useful. We develop a new method for transfer le...
Ariadna Quattoni, Michael Collins, Trevor Darrell
CVPR
2001
IEEE
14 years 9 months ago
Learning Models for Object Recognition
We consider learning models for object recognition from examples. Our method is motivated by systems that use the Hausdorff distance as a shape comparison measure. Typically an ob...
Pedro F. Felzenszwalb
ICML
2005
IEEE
14 years 8 months ago
High speed obstacle avoidance using monocular vision and reinforcement learning
We consider the task of driving a remote control car at high speeds through unstructured outdoor environments. We present an approach in which supervised learning is first used to...
Jeff Michels, Ashutosh Saxena, Andrew Y. Ng