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Specifically, the main objective is to classify frame by frame personal video recordings into 24 semantically meaningful categories.
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Support vector machines trained on spectral features are used to classify frame-level note instances.
The trained SVM model can classify frames of separated sounds into voice or non-voice.
In analogy with the neurometric curves, for each stimulus type, we then trained a linear discriminant (leave-one-out cross-validation procedure) to classify frames into those that were recorded during trials where a 'short' or 'long' stimulus interval was presented.
EDCA provides service differentiation by classifying frames from upper layers in different access categories (ACs).
In the case of local motion, the algorithm detected skin segments, and utilized edge moments to classify each frame as an objectionable or a benign frame.
type (1 byte): this field is used to classify the frame by the step of the algorithm which it belongs to.
We have used the frame structure in Fig. 2. Note that not all the fields are required for an implementation but are useful for monitoring purposes: type (1 byte): this field is used to classify the frame by the step of the algorithm which it belongs to.
Genotype counts per individual for sites classified as frame shift and in-frame mutations (loss of function).
We use a supervised learning algorithm to classify spectrogram frames extracted from digital audio as being onsets or nononsets.
Syntactic grooming chains were identified and classified in frame-by-frame analysis as either Perfect, Imperfect but completed by full Phase IV (omission, insertion, or reversal types), Terminal substitution of paw lick for Phase IV body licking, or Incomplete (grooming stops before Phase IV, or reverts to sequentially flexible facial grooming and paw strokes) [ 37, 41], [ 43, 44].
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