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Feature vector

Known as: Feature space, Attribute construction, Feature construction 
In pattern recognition and machine learning, a feature vector is an n-dimensional vector of numerical features that represent some object. Many… 
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Related topics

Related topics

34 relations
AlgorithmAutomatic image annotationBIRCHBinary classification

Broader (2)

Data miningMachine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2012
Highly Cited
2012
A Model-Based Shot Boundary Detection Technique Using Frame Transition Parameters
We have presented a unified model for detecting different types of video shot transitions. Based on the proposed model, we… 
Highly Cited
2010
Highly Cited
2010
Uncorrelated Discriminant Nearest Feature Line Analysis for Face Recognition
We propose in this letter a new subspace learning method, called uncorrelated discriminant nearest feature line analysis (UDNFLA… 
Highly Cited
2010
Highly Cited
2010
A Stochastic Approach to Image Retrieval Using Relevance Feedback and Particle Swarm Optimization
Understanding the subjective meaning of a visual query, by converting it into numerical parameters that can be extracted and… 
Highly Cited
2007
Highly Cited
2007
Statistical Pattern Recognition and Built-in Reliability Test for Feature Extraction and Health Monitoring of Electronics Under Shock Loads
The built-in stress test (BIST) is extensively used for diagnostics or identification of failure. The current version of BIST… 
Highly Cited
2005
Highly Cited
2005
Nonlinear Discriminant Analysis Using Kernel Functions and the Generalized Singular Value Decomposition
Linear discriminant analysis (LDA) has been widely used for linear dimension reduction. However, LDA has limitations in that one… 
Highly Cited
2005
Highly Cited
2005
Visual quality measures for Characterizing Planar robot grasps
This paper presents and analyzes 12 quality measures that characterize robotic grips according to their stability and reliability… 
Review
2000
Review
2000
Novelty detection for the identification of abnormalities
The principle of novelty detection offers an approach to the problem of fault detection which only requires the normal class to… 
Highly Cited
1995
Highly Cited
1995
Classifier and shift-invariant automatic target recognition neural networks
Highly Cited
1992
Highly Cited
1992
Improved acoustic modeling for large vocabulary continuous speech recognition
Highly Cited
1990
Highly Cited
1990
Automated design of linear tree classifiers
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