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» Mining images on semantics via statistical learning
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ICIP
2006
IEEE
14 years 9 months ago
Unsupervised Image Layout Extraction
We propose a novel unsupervised learning algorithm to extract the layout of an image by learning latent object-related aspects. Unlike traditional image segmentation algorithms th...
David Liu, Datong Chen, Tsuhan Chen
TIP
2010
255views more  TIP 2010»
13 years 2 months ago
Image Super-Resolution Via Sparse Representation
This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests that image patches can be wellrepre...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma
ECCV
2006
Springer
14 years 9 months ago
Scene Classification Via pLSA
Given a set of images of scenes containing multiple object categories (e.g. grass, roads, buildings) our objective is to discover these objects in each image in an unsupervised man...
Anna Bosch, Andrew Zisserman, Xavier Muñoz
SDM
2012
SIAM
278views Data Mining» more  SDM 2012»
11 years 9 months ago
Legislative Prediction via Random Walks over a Heterogeneous Graph
In this article, we propose a random walk-based model to predict legislators’ votes on a set of bills. In particular, we first convert roll call data, i.e. the recorded votes a...
Jun Wang, Kush R. Varshney, Aleksandra Mojsilovic
IJCNLP
2005
Springer
14 years 27 days ago
Automatic Image Annotation Using Maximum Entropy Model
Automatic image annotation is a newly developed and promising technique to provide semantic image retrieval via text descriptions. It concerns a process of automatically labeling t...
Wei Li, Maosong Sun