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» The Skip-Innovation Model for Sparse Images
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ICML
2010
IEEE
13 years 8 months ago
Proximal Methods for Sparse Hierarchical Dictionary Learning
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
Rodolphe Jenatton, Julien Mairal, Guillaume Obozin...
ECCV
2010
Springer
14 years 21 days ago
Face Liveness Detection from A Single Image with Sparse Low Rank Bilinear Discriminative Model
Spoofing with photograph or video is one of the most common manner to circumvent a face recognition system. In this paper, we present a real-time and non-intrusive method to addre...
MICCAI
2010
Springer
13 years 5 months ago
Understanding the Optics to Aid Microscopy Image Segmentation
Abstract. Image segmentation is essential for many automated microscopy image analysis systems. Rather than treating microscopy images as general natural images and rushing into th...
Zhaozheng Yin, Kang Li, Takeo Kanade, Mei Chen
ICASSP
2011
IEEE
12 years 11 months ago
Denoising sparse noise via online dictionary learning
The idea of learning overcomplete dictionaries based on the paradigm of compressive sensing has found numerous applications, among which image denoising is considered one of the m...
Anoop Cherian, Suvrit Sra, Nikolaos Papanikolopoul...
ECCV
2002
Springer
14 years 9 months ago
Statistical Modeling of Texture Sketch
Recent results on sparse coding and independent component analysis suggest that human vision first represents a visual image by a linear superposition of a relatively small number ...
Ying Nian Wu, Song Chun Zhu, Cheng-en Guo