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* [[Resampling (statistics)]]
* Hop-Diffusion Monte Carlo uses randomized sampling involve global jumps and local diffusion to choose the sample at each step of RANSAC for epipolar geometry estimation between very wide-baseline images.<ref>{{cite journal |last1=Brahmachari |first1=Aveek S. |last2=Sarkar |first2=Sudeep |title=Hop-Diffusion Monte Carlo for Epipolar Geometry Estimation between Very Wide-Baseline Images |journal=IEEE Transactions on Pattern Analysis and Machine Intelligence |date=March 2013 |volume=35 |issue=3 |pages=755–762 |doi=10.1109/TPAMI.2012.227|pmid=26353140 |s2cid=2524656 }}</ref>
* [[FSASAC]] (RANSAC based on data filtering and [[simulated annealing]])<ref>W. Ruoyan and W. Junfeng, "[https://ieeexplore.ieee.org/document/9648331 FSASAC: Random Sample Consensus Based on Data Filter and Simulated Annealing]," in IEEE Access, vol. 9, pp. 164935-164948, 2021, doi: 10.1109/ACCESS.2021.3135416.</ref>
== See also ==
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