Introduction: Brain Computer Interface (BCI) systems based on Movement Imagination (MI) are widely used in recent decades. Separate feature extraction methods are employed in the MI data sets and classified in Virtual Reality (VR) environments for real-time applications. Methods: This study applied wide variety of features on the recorded data using Linear Discriminant Analysis (LDA) classifie...

In this paper our main aim to provide the difference between cepstral and non-cepstral feature extraction techniques. Here we try to cover-up most of the comparative features of Mel Frequency Cepstral Coefficient and prosodic features. In speaker recognition, there are two type of techniques are available for feature extraction: Short-term features i.e. Mel Frequency Cepstral Coefficient (MFCC)...

Entity recognition and entity relationship extraction are two very important tasks in information extraction. This paper proposes a new method for performing entity recognition and entity relationship extraction concurrently from unstructured text based on Conditional Random Fields (CRFs). This method makes use of entity features, entity relationship features and features of triples which is co...

Feature extraction is an important part of object model acquisition and object recognition systems. Global features describing properties of whole objects, or local features denoting the constituent parts of objects and their relationships may be used. When a model acquisition or object recognition system requires symbolic input, the features should be represented in symbolic form. Global featu...

This study investigates the use of unsupervised features derived from word embedding approaches and novel sequence representation approaches for improving clinical information extraction systems. Our results corroborate previous findings that indicate that the use of word embeddings significantly improve the effectiveness of concept extraction models; however, we further determine the influence...

In this paper we present Document analysis and classification system to segment and classify contents of Arabic document images. This system includes preprocessing, document segmentation, feature extraction and document classification. A document image is enhanced in the preprocessing by removing noise, binarization, and detecting and correcting image skew. In document segmentation, an algorith...

This paper presents the study reports of major process involved in a handwritten character recognition system. We focus on the various feature extraction techniques as the recognition mainly depends on the features extraction. After studying the various features we have modified an existing feature extraction technique by introducing two more feature vectors. After the introduction of these two...

In this paper we propose an automatic term extraction approach that uses machine learning incorporating varied and rich features of candidate terms. In our preliminary experiments, we also tested different attribute selection methods to verify which features are more relevant for automatic term extraction. We achieved state of the art results for unigram extraction in Brazilian Portuguese.

Feature extraction assumes a number of forms in a number of applications. In this paper, we improve feature extraction by not only increasing the number of quality features that one can extract but also ensuring that the features we do extract are, indeed, representative high-quality features instead of false, minute, or noise features. We show that higher frequencies do not, for the purposes o...

Today, automatic extraction of high-level audio features suffers from two main scalability issues. First, the extraction algorithms are very demanding in terms of memory and computation resources. Second, copyright laws prevent the audio files to be shared among computers, limiting the use of existing distributed computation frameworks and reducing the transparency of the methods evaluation pro...