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Although the interface method is rather different, there remains a speed/accuracy trade-off that can be optimized using some of the methods reported here.
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SVMs have several hyperparameters that need to be optimized using separate testing data.
In contrast to MonoSLAM, 3D points of feature points are optimized using lobal BA with some keyframes and global BA with all keyframes with the map.
Mg2+ concentration was optimized using the condition determined to be optimal in the previous section.
The model Equation 4 is optimized using a multistage Monte-Carlo optimization technique[43].
The objective function is optimized using non-linear, multi-resolution optimization techniques.
Some immobilization variables were optimized using statistical factorial design (Central Composite Design).
PCR assays were optimized using gradient PCRs to determine the optimal annealing temperature and primer concentration.
Model parameters were optimized using scikit-learn's GridSearch function with cross-validation.
Molecular structures were optimized using DFT B3LYP/6-31 + G(d).
Enzyme production was optimized using statistical approach.
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