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Spatial and intensity normalisation was applied to images before training the algorithm.
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Before training the compact model, a state level segmentation is made using the Viterbi algorithm with the backend model, i.e., the segmentation specifies the alignment between the states and the frames of the training data.
The research involved showing people images, one after another, and asking them to press a key when they encounter an image they had seen before to create a memorability score for images used to train the algorithm.
That way you can train the algorithm what to hide in the future.
Google says it has trained the algorithm to recognize "thousands" of different objects.
Firstly, the subtle abnormalities in the brain were identified by a pediatric neuroradiologist, before these were transformed into a range of features, including the thickness and folding of the brain, that could be used to train the algorithm.
They then use the labelling of the content moderators to train the algorithm.
Then they trained the algorithms to understand what was meant.
(5) To train the recognition algorithm on the training set.
Google says it used feedback from Voice users to train the new algorithm.
MZ trained the Random Forest algorithm and performed the RF predictions.
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