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The proposed method is applied to the recognition of medical images.
In the literature, different machine learning solutions have been applied to the recognition of activities including Naive Bayes [3], Decision Trees [4], Support Vector Machines (SVMs) [5], Deep Neural Networks [6] and Hidden Markov Models (HMMs) [7].
An e-value cut off of 1e−5 was applied to the recognition.
The present study investigated how a hybrid of categorical and dimensional theories can be applied to the recognition of facial expressions.
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We propose that this mechanism also applies to the recognition of other modifications close to the nucleosome core, such as H4K20me and H3K79me.
Similar considerations apply to the recognition of HPVs as the cause of cervical cancer and to the development of a vaccine that is now on its way to prevent the disease both in the North and the South.
The proposed hardware (called neuromolecular hardware), is the integration of inter- and intraneuronal information processing applied to the pattern recognition problem domain.
The contrasts were applied to the local recognition of mouse serum proteins adsorbed on GPTMS functionalized PSi through an immunofluorescence assay.
An e-value cutoff of 10-5 wappliedied to the homolog recognition.
An e-value cut-off of 10-10 wappliedied to the homologue recognition.
An e-value cut-off of 1e 10 was applied to the homologue recognition.
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