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CVPR
2012
IEEE
11 years 10 months ago
Unsupervised feature learning framework for no-reference image quality assessment
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
Peng Ye, Jayant Kumar, Le Kang, David S. Doermann
ICCV
2009
IEEE
15 years 17 days ago
Structure- and Motion-adaptive Regularization for High Accuracy Optic Flow
The accurate estimation of motion in image sequences is of central importance to numerous computer vision applications. Most competitive algorithms compute flow fields by minimi...
Andreas Wedel, Daniel Cremers, Thomas Pock, Horst ...
TIP
2002
123views more  TIP 2002»
13 years 7 months ago
A doubly adaptive approach to dynamic MRI sequence estimation
Dynamic magnetic resonance imaging (MRI) refers to the acquisition of a sequence of MRI images to monitor temporal changes in tissue structure. In this paper we present a method fo...
William Scott Hoge, Eric L. Miller, Hanoch Lev-Ari...
ICTAI
2010
IEEE
13 years 4 months ago
Unsupervised Greedy Learning of Finite Mixture Models
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expe...
Nicola Greggio, Alexandre Bernardino, Cecilia Lasc...
TIP
2011
123views more  TIP 2011»
13 years 2 months ago
Spatial Sparsity-Induced Prediction (SIP) for Images and Video: A Simple Way to Reject Structured Interference
We propose a prediction technique that is geared toward forming successful estimates of a signal based on a correlated anchor signal that is contaminated with complex interference...
Gang Hua, Onur G. Guleryuz