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» An Experimental Comparison of Stereo Algorithms
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IJIT
2004
15 years 3 months ago
A Comparison of First and Second Order Training Algorithms for Artificial Neural Networks
Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no expli...
Syed Muhammad Aqil Burney, Tahseen Ahmed Jilani, C...
109
Voted
BMCBI
2005
112views more  BMCBI 2005»
15 years 1 months ago
Vector analysis as a fast and easy method to compare gene expression responses between different experimental backgrounds
Background: Gene expression studies increasingly compare expression responses between different experimental backgrounds (genetic, physiological, or phylogenetic). By focusing on ...
Rainer Breitling, Patrick Armengaud, Anna Amtmann
112
Voted
ECCV
2002
Springer
16 years 3 months ago
A Comparison of Search Strategies for Geometric Branch and Bound Algorithms
Over the last decade, a number of methods for geometric matching based on a branch-and-bound approach have been proposed. Such algorithms work by recursively subdividing transforma...
Thomas M. Breuel
119
Voted
SIGMOD
2010
ACM
277views Database» more  SIGMOD 2010»
15 years 6 months ago
A comparison of join algorithms for log processing in MaPreduce
The MapReduce framework is increasingly being used to analyze large volumes of data. One important type of data analysis done with MapReduce is log processing, in which a click-st...
Spyros Blanas, Jignesh M. Patel, Vuk Ercegovac, Ju...
107
Voted
CVPR
2008
IEEE
15 years 8 months ago
Global stereo reconstruction under second order smoothness priors
Second-order priors on the smoothness of 3D surfaces are a better model of typical scenes than first-order priors. However, stereo reconstruction using global inference algorithm...
Oliver J. Woodford, Philip H. S. Torr, Ian D. Reid...