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The method adopts a two-stage approach.
The systematic review method adopts a rigorous procedure with the definition of a formal review protocol.
Their method adopts a Kalman filter with additional independence constraint between the states (sources).
This method adopts a wrapper approach with pre-specified subset channel selection depending on experience.
Their method adopts a patch-based greedy sampling algorithm, and faster and simpler inpainting becomes feasible.
Compared with other methods, the proposed method adopts a lower number instead of numerous codewords.
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The proposed method adopts an energy function which includes a data constraint term and a gradient constraint term.
Based on discrete Gaussian curvatures, the second method adopts an angle deficit algorithm for discrete Gaussian curvatures approximation.
This method adopted a wrapper approach with a random search strategy for subset channel selection.
To motivate the recruiting of respondents and reduce the sampling bias, the RDS method adopted a dual-incentive strategy that provided material incentives for both respondents and recruiters.
In addition to the estimation of q itself, it should be noted that our method adopted an assumption that the pre-existing immunity offered a complete protection from infection (i.e. all-or-nothing protection).
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