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» Object correspondence as a machine learning problem
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CVPR
2010
IEEE
15 years 10 months ago
Boundary Learning by Optimization with Topological Constraints
Recent studies have shown that machine learning can improve the accuracy of detecting object boundaries in images. In the standard approach, a boundary detector is trained by mini...
Viren Jain, Benjamin Bollmann, Bobby Kasthuri, Ken...
JMLR
2012
13 years 4 months ago
Online Incremental Feature Learning with Denoising Autoencoders
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
Guanyu Zhou, Kihyuk Sohn, Honglak Lee
ICRA
2007
IEEE
189views Robotics» more  ICRA 2007»
15 years 8 months ago
Context Estimation and Learning Control through Latent Variable Extraction: From discrete to continuous contexts
— Recent advances in machine learning and adaptive motor control have enabled efficient techniques for online learning of stationary plant dynamics and it’s use for robust pre...
Georgios Petkos, Sethu Vijayakumar
ICIP
2007
IEEE
16 years 3 months ago
Determining Topology in a Distributed Camera Network
Recently, `entry/exit' events of objects in the field-of-views of cameras were used to learn the topology of the camera network. The integration of object appearance was also...
Xiaotao Zou, Bir Bhanu, Bi Song, Amit K. Roy Chowd...
ICCV
2011
IEEE
14 years 1 months ago
Discriminative Learning of Relaxed Hierarchy for Large-scale Visual Recognition
In the real visual world, the number of categories a classifier needs to discriminate is on the order of hundreds or thousands. For example, the SUN dataset [24] contains 899 sce...
Tianshi Gao, Daphne Koller