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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
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Broader (2)

Data miningMachine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2010
Review
2010
A Survey on Transfer Learning
A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same… 
Highly Cited
2004
Highly Cited
2004
Support-Vector Networks
The support-vector network is a new learning machine for two-group classification problems. The machine conceptually implements… 
Highly Cited
2004
Highly Cited
2004
Distinctive Image Features from Scale-Invariant Keypoints
This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable… 
Highly Cited
2004
Highly Cited
2004
Support-vector networks
Thesupport-vector network is a new learning machine for two-group classification problems. The machine conceptually implements… 
Highly Cited
2004
Highly Cited
2004
Distinctive Image Features from Scale-Invariant Keypoints
  • D. Lowe
  • International Journal of Computer Vision
  • 2004
  • Corpus ID: 221242327
This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable… 
Highly Cited
2003
Highly Cited
2003
An Introduction to Variable and Feature Selection
Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or… 
Highly Cited
2001
Highly Cited
2001
Efficient Iris Recognition through Improvement of Feature Vector and Classifier
In this paper, we propose an efficient method for personal identification by analyzing iris patterns that have a high level of… 
Highly Cited
1998
Highly Cited
1998
Feature Selection via Concave Minimization and Support Vector Machines
Computational comparison is made between two feature selection approaches for nding a separating plane that discriminates between… 
Highly Cited
1997
Highly Cited
1997
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
We develop a face recognition algorithm which is insensitive to large variation in lighting direction and facial expression… 
Highly Cited
1996
Highly Cited
1996
Support Vector Regression Machines
A new regression technique based on Vapnik's concept of support vectors is introduced. We compare support vector regression (SVR… 
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