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What is Feature Extraction
1.
Transformation of input data into a set of
feature
s.
Feature
s 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
2.
An algorithm to extract distinctive values from signal.
Learn more in: Acoustic Presence Detection in a Smart Home Environment
3.
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
4.
It is a process that starts with the initial set of measured data and builds derived values intended to be informative.
Learn more in: Voice-Based Speaker Identification and Verification
5.
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
6.
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
7.
It is a dimensionality reduction process, where an initial set of raw variables is reduced to more manageable groups or
feature
s.
Learn more in: Heart Sound Data Acquisition and Preprocessing Techniques: A Review
8.
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
9.
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
10.
It is a process of deriving new
feature
s from the original
feature
s 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
11.
Transforming the input data into the set of
feature
s is called
feature extraction
. If the
feature
s extracted are carefully chosen, it is expected that the
feature
s 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
12.
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
13.
When the data is too large to be processed, the data will be transformed into a reduced representation set of
feature
s. The process of transforming the input data into the set of
feature
s is called
feature extraction
.
Learn more in: A Novel Fuzzy Logic Classifier for Classification and Quality Measurement of Apple Fruit
14.
Extraction
of representative properties of an object for the purpose of classification.
Learn more in: Computational Models for the Analysis of Modern Biological Data
15.
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
16.
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
17.
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
18.
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
19.
The process by which a new set of discriminative
feature
s is obtained from those available. Classification is performed using the new set of
feature
s.
Learn more in: Component Analysis in Artificial Vision
20.
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
21.
Process of reducing data by measuring certain properties or
feature
s. These
feature
s are used in a classifier.
Learn more in: In Machina Systems for the Rational De Novo Peptide Design
22.
Feature extraction
is the process of transforming the input data into a set of
feature
s 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
23.
It is the name for methods that select and /or combine variables into
feature
s, 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
24.
The process of extracting and building
feature
s from raw data such as the amino acid sequence of a protein.
Feature
functions are utilized to extract and process informative
feature
s that are useful for prediction.
Learn more in: Computer Aided Knowledge Discovery in Biomedicine
25.
Finding of representative
feature
s of a determined problem from samples with different characteristics.
Learn more in: Artificial Intelligence in Computer-Aided Diagnosis
26.
Feature extraction
is a procedure in dimensionality reduction of extracting principal variables (
feature
s) 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
27.
Method or algorithm which analyses music and computes (extracts)
feature
s from it.
Learn more in: Music Information Retrieval
28.
Step prior to model training that removes
feature
s that have minor impact on the outcome.
Learn more in: Scientific Applications of Machine Learning Algorithms
29.
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
30.
A process of finding
feature
s of words and map them to vector space.
Learn more in: Machine Learning in Text Analysis
31.
Mapping a multimedia object to
feature
s.
Learn more in: Multimedia Representation
32.
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
33.
Feature extraction
transforms an input image into a set of
feature
s.
Learn more in: Biometric Technologies in Healthcare Biometrics
34.
The process of detection, isolation and
extraction
of various desired portions or
feature
s of a digitized image.
Learn more in: Ant Colony Optimization for Use in Content Based Image Retrieval
35.
The process of selecting a subset of variables that are used in the constructing of the
feature
vector.
Learn more in: Interpreting Brain Waves
36.
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
37.
A dimensionality reduction method that finds a reduced set of
feature
s that are a combination of the original ones.
Learn more in: Feature Selection
38.
Is a process of dimensionality reduction which defines manageable resources to describe an initial large raw data set.
Learn more in: Behavior Classification of Egyptian Fruit Bat (Rousettus aegyptiacus) From Calls With Deep Learning
39.
When the data is too large to be processed, the data will be transformed into a reduced representation set of
feature
s. The process of transforming the input data into the set of
feature
s is called
feature extraction
.
Learn more in: Collective Event Detection by a Distributed Low-Cost Smart Camera Network
40.
In machine learning,
feature extraction
starts from an initial set of measured data and builds derived values (
feature
s) 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 (
feature
s) for processing, while still accurately and completely describing the original data set.
Learn more in: Real-Time ECG-Based Biometric Authentication System
41.
A procedure to obtain specific
feature
s from the data by employing appropriate techniques.
Learn more in: XHAC: Explainable Human Activity Classification From Sensor Data
42.
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
43.
The task of generating new
feature
s by using some methods from existing information in the data.
Learn more in: Animal Activity Recognition From Sensor Data Using Ensemble Learning
44.
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
Find more terms and definitions using our
Dictionary Search
.
Feature Extraction
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