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» Learning Iterative Image Reconstruction
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196
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BDA
2007
15 years 2 months ago
Hyperplane Queries in a Feature-Space M-tree for Speeding up Active Learning
In content-based retrieval, relevance feedback (RF) is a noticeable method for reducing the “semantic gap” between the low-level features describing the content and the usually...
Michel Crucianu, Daniel Estevez, Vincent Oria, Jea...
140
Voted
SIAMIS
2011
14 years 7 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
150
Voted
CW
2008
IEEE
15 years 7 months ago
Automatic Surface Scanning of 3D Artifacts
—This paper describes an automatic 3D surface scanning technique using a 3D scanner. It allows the acquisition of a complete surface model of a 3D artifact without any manual reg...
Shiaofen Fang, Basil George, Mathew Palakal
ICRA
2007
IEEE
225views Robotics» more  ICRA 2007»
15 years 7 months ago
Accurate Quadrifocal Tracking for Robust 3D Visual Odometry
— This paper describes a new image-based approach to tracking the 6dof trajectory of a stereo camera pair using a corresponding reference image pairs instead of explicit 3D featu...
Andrew I. Comport, Ezio Malis, Patrick Rives
139
Voted
ECCV
2002
Springer
16 years 2 months ago
Assorted Pixels: Multi-sampled Imaging with Structural Models
Abstract. Multi-sampled imaging is a general framework for using pixels on an image detector to simultaneously sample multiple dimensions of imaging (space, time, spectrum, brightn...
Shree K. Nayar, Srinivasa G. Narasimhan