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» Latent Semantic Indexing: A Probabilistic Analysis
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MM
2009
ACM
269views Multimedia» more  MM 2009»
13 years 12 months ago
Semi-supervised topic modeling for image annotation
We propose a novel technique for semi-supervised image annotation which introduces a harmonic regularizer based on the graph Laplacian of the data into the probabilistic semantic ...
Yuanlong Shao, Yuan Zhou, Xiaofei He, Deng Cai, Hu...
MM
2005
ACM
209views Multimedia» more  MM 2005»
13 years 11 months ago
Learning an image-word embedding for image auto-annotation on the nonlinear latent space
Latent Semantic Analysis (LSA) has shown encouraging performance for the problem of unsupervised image automatic annotation. LSA conducts annotation by keywords propagation on a l...
Wei Liu, Xiaoou Tang
LREC
2008
153views Education» more  LREC 2008»
13 years 6 months ago
Using Random Indexing to improve Singular Value Decomposition for Latent Semantic Analysis
We present results from using Random Indexing for Latent Semantic Analysis to handle Singular Value Decomposition tractability issues. We compare Latent Semantic Analysis, Random ...
Linus Sellberg, Arne Jönsson
MM
2003
ACM
132views Multimedia» more  MM 2003»
13 years 10 months ago
On image auto-annotation with latent space models
Image auto-annotation, i.e., the association of words to whole images, has attracted considerable attention. In particular, unsupervised, probabilistic latent variable models of t...
Florent Monay, Daniel Gatica-Perez
ICPR
2006
IEEE
14 years 6 months ago
Latent Layout Analysis for Discovering Objects in Images
Latent Layout Analysis (LLA) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. LLA defines a generative ...
David Liu, Datong Chen, Tsuhan Chen