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It consists of two main modules: feature extraction and machine learning algorithm for activity classification.
Existing methods for music auto-tagging usually consist of preprocessing phase (feature extraction) and machine learning phase.
This paper introduces the first application of feature extraction and machine learning to electromagnetic interference (EMI) signals for discharge sources classification in high voltage power generating plants.
To overcome the limitations in manual inspection, feature extraction and machine learning methods have recently been used in automatic staining pattern classification of HEp-2 cells.
Therefore, in this study, we investigate into the feature extraction and machine learning methods for automatic staining pattern classification of HEp-2 cells.
By use of a novel software package based on image analysis, feature extraction and machine learning algorithms, relevant characteristics describing patterns could be found out.
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Advanced NLP applications rely on entity and relationship extraction and on machine learning (ML).
FunGramKB is a multilingual and multipurpose lexico-conceptual knowledge-base designed for its use in various tasks in Natural Language Processing (NLP), like information extraction and retrieval, machine translation or artificial reasoning (Periñán and Arcas, 2004; Mairal and Periñán, 2009; 2010).
Text analytics covers natural language processing (NLP), information extraction, data mining, and machine learning approaches [23].
The image processing combined two usual methods, which are spectral feature extraction and support vector machine (SVM).
Song and Liò [29] developed an EEG epilepsy detection scheme based on the entropy-based feature extraction and extreme learning machine.
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