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The second comparison algorithm is a window-based stereo matching algorithm based on the SSIM [34] index (DSSIM) [20].
In this paper we present a matching algorithm based on a fixpoint computation that is usable across different scenarios.
A stereo matching algorithm based on dual-band images is proposed as well.
A matching algorithm based on area and epipolar geometry was discussed to locate the apples.
Finally, a matching algorithm based on pixel-to-area comparison has been designed, which has better fault tolerant ability.
In this work, a new automatic history matching algorithm based on B-spline representation was applied to estimate pseudo relative permeability curves.
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We propose a very fast new family of string matching algorithms based on hashing q-grams.
We adapt two classical approximate string matching algorithms based on automata simulation and bit-vector processing to efficiently identify exact and approximate occurrences of motifs.
Recently, string matching algorithms based on the Burrow-Wheeler Transformation (BWT) [14], which is a string compression technique, has drawn the attention of many research groups.
We have previously presented a new scan-matching algorithm based on the IDC (iterative dual correspondence) algorithm, which showed a good localization performance even in environments with severe changes.
In this paper, we propose a fast block-matching algorithm based on search center prediction and search early termination, called center-prediction and early-termination based motion search algorithm (CPETS).
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