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» Image Categorization Using Local Probabilistic Descriptors
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CIVR
2008
Springer
222views Image Analysis» more  CIVR 2008»
13 years 10 months ago
Automatic image annotation via local multi-label classification
As the consequence of semantic gap, visual similarity does not guarantee semantic similarity, which in general is conflicting with the inherent assumption of many generativebased ...
Mei Wang, Xiangdong Zhou, Tat-Seng Chua
CVPR
2011
IEEE
13 years 5 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
SISAP
2010
IEEE
259views Data Mining» more  SISAP 2010»
13 years 7 months ago
kNN based image classification relying on local feature similarity
In this paper, we propose a novel image classification approach, derived from the kNN classification strategy, that is particularly suited to be used when classifying images descr...
Giuseppe Amato, Fabrizio Falchi
VLSISP
2010
254views more  VLSISP 2010»
13 years 7 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
DAGM
2004
Springer
14 years 2 months ago
A Probabilistic Framework for Robust and Accurate Matching of Point Clouds
We present a probabilistic framework for matching of point clouds. Variants of the ICP algorithm typically pair points to points or points to lines. Instead, we pair data points to...
Peter Biber, Sven Fleck, Wolfgang Straßer