What is Feature Extraction

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Transformation of input data into a set of features. Features are distinctive properties of input patterns that help in differentiating between the categories of input patterns. Learn more in: Non-Manual Control Devices: Direct Brain-Computer Interaction

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An algorithm to extract distinctive values from signal. Learn more in: Acoustic Presence Detection in a Smart Home Environment

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A digital signal processing algorithm, which extracts distinctive values from the input signal. Learn more in: Embodied Conversation: A Personalized Conversational HCI Interface for Ambient Intelligence

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It is a method frequently used in learning and image processing applications. In the field of text mining, it can be thought of as obtaining the words in the document. Learn more in: An Extensive Text Mining Study for the Turkish Language: Author Recognition, Sentiment Analysis, and Text Classification

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Quantification of image content by means of computer algorithms, aiming to capture tissue alterations, due to underlying biological processes reflected either as morphology or as texture variations, mimicking or complementing radiologist interpretation, used in subsequent pattern analysis. Learn more in: Computer-Aided Diagnosis in Breast Imaging: Trends and Challenges

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It is a dimensionality reduction process, where an initial set of raw variables is reduced to more manageable groups or features. Learn more in: Heart Sound Data Acquisition and Preprocessing Techniques: A Review

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The process to represent raw image in a reduced form to facilitate decision making such as pattern detection, classification or recognition. Learn more in: Feature Extraction Techniques: Fundamental Concepts and Survey

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A technique that reduces the amount of input data by distilling its representative descriptive attributes. Learn more in: Using Supervised Machine Learning to Explore Energy Consumption Data in Private Sector Housing

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It is a process of deriving new features from the original features in order to reduce the cost of feature measurement, increase classifier efficiency, and allow higher classification accuracy. Learn more in: Big Data Mining Based on Computational Intelligence and Fuzzy Clustering

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Transforming the input data into the set of features is called feature extraction. If the features extracted are carefully chosen, it is expected that the features set will perform the desired task using the reduced representation instead of the full size input. Learn more in: Computational Intelligence for Pathological Issues in Precision Agriculture

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Feature extraction refers to the extraction of linguistic items from the documents to provide a representative sample of their content. Distinctive vocabulary items found in a document are assigned to the different categories by measuring the importance of those items to the document content. Learn more in: Text Mining

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When the data is too large to be processed, the data will be transformed into a reduced representation set of features. The process of transforming the input data into the set of features is called feature extraction. Learn more in: A Novel Fuzzy Logic Classifier for Classification and Quality Measurement of Apple Fruit

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Extraction of representative properties of an object for the purpose of classification. Learn more in: Computational Models for the Analysis of Modern Biological Data

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A subject of multimedia processing which involves applying algorithms to calculate and extract some attributes for describing the media. Learn more in: Content-Based Multimedia Retrieval

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It is a process for extracting relevant information from an image. After detecting a face, some valuable information are extracted from the image which are used in next step for identifying the image. Learn more in: Application of Face Recognition Techniques in Video for Biometric Security: A Review of Basic Methods and Emerging Trends

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This is a process which is used to obtain certain characteristics which are intrinsic and discriminate of a thing. Learn more in: State of the Art in Writer's Off-Line Identification

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A common step in most image processing applications, where the image is pre-processed in order to come up with those aspects of the image that uniquely characterize a given image (for an image classification application, for instance). In most image processing applications, not all parts of the image are equally important. Feature extraction is therefore employed in order to take advantage of this fact and reduce the computational burden. Learn more in: On the Use of Artificial Intelligence Techniques in Crop Monitoring and Disease Identification

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The process by which a new set of discriminative features is obtained from those available. Classification is performed using the new set of features. Learn more in: Component Analysis in Artificial Vision

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The process of detection and description of global or local properties of objects present in images. Learn more in: Automatic Target Recognition from Inverse Synthetic Aperture Radar Images

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Process of reducing data by measuring certain properties or features. These features are used in a classifier. Learn more in: In Machina Systems for the Rational De Novo Peptide Design

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Feature extraction is the process of transforming the input data into a set of features which can very well represent the input data. It is a special form of dimensionality reduction. Learn more in: Soft-Computational Techniques and Spectro-Temporal Features for Telephonic Speech Recognition: An Overview and Review of Current State of the Art

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It is the name for methods that select and /or combine variables into features, effectively reducing the amount of data that must be processed, while still accurately and completely describing the original data set. Learn more in: Automatic Detection and Assessment of Autism Spectrum Disorder: A Systematic Review

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The process of extracting and building features from raw data such as the amino acid sequence of a protein. Feature functions are utilized to extract and process informative features that are useful for prediction. Learn more in: Computer Aided Knowledge Discovery in Biomedicine

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Finding of representative features of a determined problem from samples with different characteristics. Learn more in: Artificial Intelligence in Computer-Aided Diagnosis

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Feature extraction is a procedure in dimensionality reduction of extracting principal variables (features) from some random variables under consideration, usually achieved by extracting one principal variable (feature) as mapping from multiple random variables. Learn more in: Reevaluating Factor Models: Feature Extraction of the Factor Zoo

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Method or algorithm which analyses music and computes (extracts) features from it. Learn more in: Music Information Retrieval

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A process of extracting the important or relevant characteristics that enclosed within the input data. Dimensionality or size of the input data will be subsequently reduced to preserve important information only. Learn more in: Automated Technology Integrations for Customer Satisfaction Assessment

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A process of finding features of words and map them to vector space. Learn more in: Machine Learning in Text Analysis

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Mapping a multimedia object to features. Learn more in: Multimedia Representation

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A method to obtain meaningful and clear data of a signal. Learn more in: General Perspectives on Electromyography Signal Features and Classifiers Used for Control of Human Arm Prosthetics

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Feature extraction transforms an input image into a set of features. Learn more in: Biometric Technologies in Healthcare Biometrics

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The process of detection, isolation and extraction of various desired portions or features of a digitized image. Learn more in: Ant Colony Optimization for Use in Content Based Image Retrieval

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The process of selecting a subset of variables that are used in the constructing of the feature vector. Learn more in: Interpreting Brain Waves

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Extracting or deriving some useful information from the initially obtained data. Learn more in: An Overview of Biomedical Image Analysis From the Deep Learning Perspective

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A dimensionality reduction method that finds a reduced set of features that are a combination of the original ones. Learn more in: Feature Selection

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When the data is too large to be processed, the data will be transformed into a reduced representation set of features. The process of transforming the input data into the set of features is called feature extraction. Learn more in: Collective Event Detection by a Distributed Low-Cost Smart Camera Network

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In machine learning, feature extraction starts from an initial set of measured data and builds derived values (features) intended to be informative and non-redundant, facilitating the subsequent learning and generalization steps, and in some cases leading to better human interpretations. Feature extraction is a dimensionality reduction process, where an initial set of raw variables is reduced to more manageable groups (features) for processing, while still accurately and completely describing the original data set. Learn more in: Real-Time ECG-Based Biometric Authentication System

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A method to obtain meaningful and clear data of a signal. Learn more in: General Perspectives on Electromyography Signal Features and Classifiers Used for Control of Human Arm Prosthetics

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It is the process to extract the main time frequency components of the signal to differentiate it from other signals. Learn more in: Three Channel Wavelet Filter Banks With Minimal Time Frequency Spread for Classification of Seizure-Free and Seizure EEG Signals