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DSP
2007
14 years 11 months ago
Blind separation of nonlinear mixtures by variational Bayesian learning
Blind separation of sources from nonlinear mixtures is a challenging and often ill-posed problem. We present three methods for solving this problem: an improved nonlinear factor a...
Antti Honkela, Harri Valpola, Alexander Ilin, Juha...
ACCV
2010
Springer
14 years 6 months ago
Optimizing Visual Vocabularies Using Soft Assignment Entropies
The state of the art for large database object retrieval in images is based on quantizing descriptors of interest points into visual words. High similarity between matching image r...
Yubin Kuang, Kalle Åström, Lars Kopp, M...
IEEEICCI
2009
IEEE
14 years 8 months ago
Learning from an ensemble of Receptive Fields
Abstract-In this paper, we construct a neural-inspired computational model based on the representational capabilities of receptive fields. The proposed model, known as Shape Encodi...
Hanlin Goh, Joo Hwe Lim, Chai Quek
82
Voted
CVPR
2008
IEEE
16 years 1 months ago
Sparsity, redundancy and optimal image support towards knowledge-based segmentation
In this paper, we propose a novel approach to model shape variations. It encodes sparsity, exploits geometric redundancy, and accounts for the different degrees of local variation...
Salma Essafi, Georg Langs, Nikos Paragios
86
Voted
TSMC
2010
14 years 5 months ago
A Unified Tensor Level Set for Image Segmentation
Abstract--This paper presents a new region-based unified tensor level set model for image segmentation. This model introduces a three-order tensor to comprehensively depict feature...
Bin Wang, Xinbo Gao, Dacheng Tao, Xuelong Li