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The statistical results of the established models are Training set: R = 0.94, s = 0.12; Test set: R = 0.81, s = 3.95.
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Models are trained not to sit down on the job.
AI and ML models are trained through the inspection of features or characteristics of the system being modeled.
The surrogate models are trained adaptively during optimization based on a genetic algorithm.
The models are trained with expectation maximisation algorithm [26] using segmented training examples.
Once the models are trained on the images, Lagerman will benchmark them against data collected from manually counting mites.
All the models are trained and tested, the results obtained are recorded.
The baseline system (linguistic models are trained on Ohm_base) is given in column "Ohm_base".
The baseline system (linguistic models are trained on Ohm_N) is given in column "Ohm_N".
SVM models are trained by the One-Against-All (OAA) method.
Person-specific models are trained from video sequences to form many individual eigenspaces in [27].
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