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What is Feature Extraction

Chapter 15
Handbook of Research on Personal Autonomy Technologies and Disability Informatics
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.
Published in Chapter:
Non-Manual Control Devices: Direct Brain-Computer Interaction
Reinhold Scherer (University of Washington, USA & Graz University of Technology, Austria & Judendorf-Strassengel Clinic, Austria) and Rajesh Rao (University of Washington, USA)
Copyright: © 2011 |Pages: 18
DOI: 10.4018/978-1-60566-206-0.ch015
Abstract
Brain-computer interface (BCI) technology augments the human capability to interact with the environment by directly linking the brain to artificial devices. The first generation of BCIs provided simple 1D control in order to select targets on a screen or trigger pre-defined motion sequences of paralyzed limbs by means of functional electrical stimulation. BCIs today can provide users on-demand access to assistive robotic devices, Virtual Reality environments, and standard software applications such as Internet browsers. Here, we introduce readers to BCIs and review basic principles and methodologies underlying their operation. We illustrate the capabilities and limitations of modern BCI systems by discussing two practical examples: BCI-based control of a humanoid robot for physical manipulation and transport of objects in an indoor environment, and BCI-based interaction with the popular global navigation program Google Earth.
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Chapter 11
Acoustic Presence Detection in a Smart Home Environment
An algorithm to extract distinctive values from signal.
Published in Chapter: Acoustic Presence Detection in a Smart Home Environment; From: Encyclopedia of Information Science and Technology, Fifth Edition
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Chapter 76
Embodied Conversation: A Personalized Conversational HCI Interface for Ambient Intelligence
A digital signal processing algorithm, which extracts distinctive values from the input signal.
Published in Chapter: Embodied Conversation: A Personalized Conversational HCI Interface for Ambient Intelligence; From: Encyclopedia of Organizational Knowledge, Administration, and Technology
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Chapter 16
Voice-Based Speaker Identification and Verification
It is a process that starts with the initial set of measured data and builds derived values intended to be informative.
Published in Chapter: Voice-Based Speaker Identification and Verification; From: Handbook of Research on Knowledge and Organization Systems in Library and Information Science
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Chapter 12
An Extensive Text Mining Study for the Turkish Language: Author Recognition, Sentiment Analysis, and Text Classification
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.
Published in Chapter: An Extensive Text Mining Study for the Turkish Language: Author Recognition, Sentiment Analysis, and Text Classification; From: Natural Language Processing for Global and Local Business
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Chapter 2
Emotion Detection and Classification Using Machine Learning Techniques
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Chapter 10
Computer-Aided Diagnosis in Breast Imaging: Trends and Challenges
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.
Published in Chapter: Computer-Aided Diagnosis in Breast Imaging: Trends and Challenges; From: Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications
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Chapter 8
Automatic Image Captioning Using Different Variants of the Long Short-Term Memory (LSTM) Deep Learning Model
The process used to convert raw data to numerical format to make it easier to process the data while retaining the information in the original dataset.
Published in Chapter: Automatic Image Captioning Using Different Variants of the Long Short-Term Memory (LSTM) Deep Learning Model; From: Deep Learning Research Applications for Natural Language Processing
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Chapter 14
Heart Sound Data Acquisition and Preprocessing Techniques: A Review
It is a dimensionality reduction process, where an initial set of raw variables is reduced to more manageable groups or features.
Published in Chapter: Heart Sound Data Acquisition and Preprocessing Techniques: A Review; From: Handbook of Research on Advancements of Artificial Intelligence in Healthcare Engineering
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Chapter 13
Plant Disease Classification Using Deep Learning Techniques
It is the process of automatically extracting or selecting a subset of relevant features or patterns from raw data, such as images or signals, to facilitate further analysis or classification. Its goal is to reduce the dimensionality of the data while preserving the most important information for downstream tasks.
Published in Chapter: Plant Disease Classification Using Deep Learning Techniques; From: Effective AI, Blockchain, and E-Governance Applications for Knowledge Discovery and Management
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Chapter 13
Feature Extraction Techniques: Fundamental Concepts and Survey
The process to represent raw image in a reduced form to facilitate decision making such as pattern detection, classification or recognition.
Published in Chapter: Feature Extraction Techniques: Fundamental Concepts and Survey; From: Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing
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Chapter 19
Using Supervised Machine Learning to Explore Energy Consumption Data in Private Sector Housing
A technique that reduces the amount of input data by distilling its representative descriptive attributes.
Published in Chapter: Using Supervised Machine Learning to Explore Energy Consumption Data in Private Sector Housing; From: Handbook of Research on Organizational Transformations through Big Data Analytics
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Chapter 7
Big Data Mining Based on Computational Intelligence and Fuzzy Clustering
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.
Published in Chapter: Big Data Mining Based on Computational Intelligence and Fuzzy Clustering; From: Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence
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Chapter 15
Building a Chatbot for Libraries
Refers to the process of manipulating data into a numerical feature that can be processed by the machine while preserving the information in the original dataset.
Published in Chapter: Building a Chatbot for Libraries; From: Handbook of Research on Advancements of Contactless Technology and Service Innovation in Library and Information Science
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Chapter 26
Computational Intelligence for Pathological Issues in Precision Agriculture
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.
Published in Chapter: Computational Intelligence for Pathological Issues in Precision Agriculture; From: Handbook of Research on Computational Intelligence for Engineering, Science, and Business
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Chapter 54
Text Mining
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.
Published in Chapter: Text Mining; From: Handbook of Research on Public Information Technology
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Chapter 17
A Novel Fuzzy Logic Classifier for Classification and Quality Measurement of Apple Fruit
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.
Published in Chapter: A Novel Fuzzy Logic Classifier for Classification and Quality Measurement of Apple Fruit; From: Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing
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Chapter 6
Computational Models for the Analysis of Modern Biological Data
Extraction of representative properties of an object for the purpose of classification.
Published in Chapter: Computational Models for the Analysis of Modern Biological Data; From: Handbook of Research on Systems Biology Applications in Medicine
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Chapter 3
Learning Framework for Real-World Facial Emotion Recognition
Feature extraction is the process of selecting and transforming raw data into a set of features, or measurable attributes, that are relevant and useful for a specific task or application. It is a common technique used in machine learning, computer vision, and signal processing to reduce the dimensionality and complexity of data while retaining important information.
Published in Chapter: Learning Framework for Real-World Facial Emotion Recognition; From: AI-Enabled Social Robotics in Human Care Services
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Chapter 36
Content-Based Multimedia Retrieval
A subject of multimedia processing which involves applying algorithms to calculate and extract some attributes for describing the media.
Published in Chapter: Content-Based Multimedia Retrieval; From: Encyclopedia of Multimedia Technology and Networking, Second Edition
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Chapter 19
Application of Face Recognition Techniques in Video for Biometric Security: A Review of Basic Methods and Emerging Trends
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.
Published in Chapter: Application of Face Recognition Techniques in Video for Biometric Security: A Review of Basic Methods and Emerging Trends; From: Handbook of Research on Modern Cryptographic Solutions for Computer and Cyber Security
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Chapter 212
State of the Art in Writer's Off-Line Identification
This is a process which is used to obtain certain characteristics which are intrinsic and discriminate of a thing.
Published in Chapter: State of the Art in Writer's Off-Line Identification; From: Encyclopedia of Artificial Intelligence
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Chapter 7
On the Use of Artificial Intelligence Techniques in Crop Monitoring and Disease Identification
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.
Published in Chapter: On the Use of Artificial Intelligence Techniques in Crop Monitoring and Disease Identification; From: Precision Agriculture Technologies for Food Security and Sustainability
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Chapter 56
Component Analysis in Artificial Vision
The process by which a new set of discriminative features is obtained from those available. Classification is performed using the new set of features.
Published in Chapter: Component Analysis in Artificial Vision; From: Encyclopedia of Artificial Intelligence
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Chapter 17
Automatic Target Recognition from Inverse Synthetic Aperture Radar Images
The process of detection and description of global or local properties of objects present in images.
Published in Chapter: Automatic Target Recognition from Inverse Synthetic Aperture Radar Images; From: Handbook of Research on Advanced Trends in Microwave and Communication Engineering
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Chapter 26
In Machina Systems for the Rational De Novo Peptide Design
Process of reducing data by measuring certain properties or features. These features are used in a classifier.
Published in Chapter: In Machina Systems for the Rational De Novo Peptide Design; From: Handbook of Research on Systems Biology Applications in Medicine
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Chapter 6
Soft-Computational Techniques and Spectro-Temporal Features for Telephonic Speech Recognition: An Overview and Review of Current State of the Art
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.
Published in Chapter: Soft-Computational Techniques and Spectro-Temporal Features for Telephonic Speech Recognition: An Overview and Review of Current State of the Art; From: Handbook of Research on Advanced Hybrid Intelligent Techniques and Applications
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Chapter 12
Severity of Breast Mass Prediction in Mammograms Based on an Optimized Naive Bayes Diagnostic System
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Chapter 20
Automatic Detection and Assessment of Autism Spectrum Disorder: A Systematic Review
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.
Published in Chapter: Automatic Detection and Assessment of Autism Spectrum Disorder: A Systematic Review; From: Handbook of Research on Critical Issues in Special Education for School Rehabilitation Practices
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Chapter 7
Computer Aided Knowledge Discovery in Biomedicine
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.
Published in Chapter: Computer Aided Knowledge Discovery in Biomedicine; From: Handbook of Research on Systems Biology Applications in Medicine
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Chapter 24
Artificial Intelligence in Computer-Aided Diagnosis
Finding of representative features of a determined problem from samples with different characteristics.
Published in Chapter: Artificial Intelligence in Computer-Aided Diagnosis; From: Encyclopedia of Artificial Intelligence
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Chapter 13
Reevaluating Factor Models: Feature Extraction of the Factor Zoo
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.
Published in Chapter: Reevaluating Factor Models: Feature Extraction of the Factor Zoo; From: Recent Applications of Financial Risk Modelling and Portfolio Management
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Chapter 46
Music Information Retrieval
Method or algorithm which analyses music and computes (extracts) features from it.
Published in Chapter: Music Information Retrieval; From: Handbook of Research on Digital Libraries: Design, Development, and Impact
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Chapter 2
The Use of Machine Learning in Libraries: How to Build a Book Recommender System
Refers to the process of manipulating data into a numerical feature that can be processed by the machine while preserving the information in the original dataset.
Published in Chapter: The Use of Machine Learning in Libraries: How to Build a Book Recommender System; From: Handbook of Research on Advancements of Contactless Technology and Service Innovation in Library and Information Science
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Chapter 4
Scientific Applications of Machine Learning Algorithms
Step prior to model training that removes features that have minor impact on the outcome.
Published in Chapter: Scientific Applications of Machine Learning Algorithms; From: Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms
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Chapter 27
Automated Technology Integrations for Customer Satisfaction Assessment
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.
Published in Chapter: Automated Technology Integrations for Customer Satisfaction Assessment; From: Handbook of Research on Managing and Influencing Consumer Behavior
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Chapter 18
Machine Learning in Text Analysis
A process of finding features of words and map them to vector space.
Published in Chapter: Machine Learning in Text Analysis; From: Handbook of Research on Emerging Trends and Applications of Machine Learning
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Chapter 135
Multimedia Representation
Mapping a multimedia object to features.
Published in Chapter: Multimedia Representation; From: Encyclopedia of Multimedia Technology and Networking, Second Edition
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Chapter 1
General Perspectives on Electromyography Signal Features and Classifiers Used for Control of Human Arm Prosthetics
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Chapter 1
Biometric Technologies in Healthcare Biometrics
Feature extraction transforms an input image into a set of features.
Published in Chapter: Biometric Technologies in Healthcare Biometrics; From: Design and Implementation of Healthcare Biometric Systems
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Chapter 8
An Investigation of AI Techniques for Detecting Kidney Stones in CT Scan Images Through Advanced Image Processing
It is a crucial step in data preprocessing, particularly in machine learning. It involves selecting relevant information from raw data to create a concise and informative representation. Techniques include dimensionality reduction, transforming data into a more manageable format, highlighting key aspects for improved model performance, and facilitating pattern recognition.
Published in Chapter: An Investigation of AI Techniques for Detecting Kidney Stones in CT Scan Images Through Advanced Image Processing; From: Enhancing Medical Imaging with Emerging Technologies
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Chapter 18
Ant Colony Optimization for Use in Content Based Image Retrieval
The process of detection, isolation and extraction of various desired portions or features of a digitized image.
Published in Chapter: Ant Colony Optimization for Use in Content Based Image Retrieval; From: Handbook of Research on Artificial Immune Systems and Natural Computing: Applying Complex Adaptive Technologies
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Chapter 30
Interpreting Brain Waves
The process of selecting a subset of variables that are used in the constructing of the feature vector.
Published in Chapter: Interpreting Brain Waves; From: Handbook of Research on Machine Learning Innovations and Trends
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Chapter 8
An Overview of Biomedical Image Analysis From the Deep Learning Perspective
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Chapter 8
Development, Monitoring, and Management Approaches of Machine Learning Implementations for the Effective Delivery of Government Services
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Chapter 13
Comprehensive Study of Face Recognition Using Feature Extraction and Fusion Face Technique
The job of discovering and extracting relevant information or features from a picture is referred to as “feature extraction,” and it is an essential one in the field of image processing.
Published in Chapter: Comprehensive Study of Face Recognition Using Feature Extraction and Fusion Face Technique; From: Concepts and Techniques of Graph Neural Networks
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Chapter 96
Feature Selection
A dimensionality reduction method that finds a reduced set of features that are a combination of the original ones.
Published in Chapter: Feature Selection; From: Encyclopedia of Artificial Intelligence
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Chapter 4
Behavior Classification of Egyptian Fruit Bat (Rousettus aegyptiacus) From Calls With Deep Learning
Is a process of dimensionality reduction which defines manageable resources to describe an initial large raw data set.
Published in Chapter: Behavior Classification of Egyptian Fruit Bat (Rousettus aegyptiacus) From Calls With Deep Learning; From: Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning
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Chapter 4
Collective Event Detection by a Distributed Low-Cost Smart Camera Network
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.
Published in Chapter: Collective Event Detection by a Distributed Low-Cost Smart Camera Network; From: Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing
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Chapter 2
Study of the Current Trends of CAD (Computer-Aided Detection) in Modern Medical Imaging
The procedure of transforming raw data into numerical features which can be managed while conserving the evidence in the new data set.
Published in Chapter: Study of the Current Trends of CAD (Computer-Aided Detection) in Modern Medical Imaging; From: Machine Learning and AI Techniques in Interactive Medical Image Analysis
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Chapter 15
Real-Time ECG-Based Biometric Authentication System
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.
Published in Chapter: Real-Time ECG-Based Biometric Authentication System; From: Countering Cyber Attacks and Preserving the Integrity and Availability of Critical Systems
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Chapter 8
XHAC: Explainable Human Activity Classification From Sensor Data
A procedure to obtain specific features from the data by employing appropriate techniques.
Published in Chapter: XHAC: Explainable Human Activity Classification From Sensor Data; From: Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics
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Chapter 24
Nighttime Object Detection: A Night-Patrolling Mechanism Using Deep Learning
For the categorization of biological signals to perform better, feature extraction and dimension reduction are necessary. Finding the most condensed and informative set of features (distinct patterns) is the goal of feature extraction in order to improve the effectiveness of the classifier.
Published in Chapter: Nighttime Object Detection: A Night-Patrolling Mechanism Using Deep Learning; From: Handbook of Research on AI Methods and Applications in Computer Engineering
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Chapter 43
General Perspectives on Electromyography Signal Features and Classifiers Used for Control of Human Arm Prosthetics
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Chapter 9
Animal Activity Recognition From Sensor Data Using Ensemble Learning
The task of generating new features by using some methods from existing information in the data.
Published in Chapter: Animal Activity Recognition From Sensor Data Using Ensemble Learning; From: Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics
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Chapter 12
Three Channel Wavelet Filter Banks With Minimal Time Frequency Spread for Classification of Seizure-Free and Seizure EEG Signals
It is the process to extract the main time frequency components of the signal to differentiate it from other signals.
Published in Chapter: Three Channel Wavelet Filter Banks With Minimal Time Frequency Spread for Classification of Seizure-Free and Seizure EEG Signals; From: Handbook of Research on Advancements of Artificial Intelligence in Healthcare Engineering
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