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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
2010
Highly Cited
2010
Learning Convolutional Feature Hierarchies for Visual Recognition
We propose an unsupervised method for learning multi-stage hierarchies of sparse convolutional features. While sparse coding has… 
Highly Cited
2007
Highly Cited
2007
Random Features for Large-Scale Kernel Machines
To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and… 
Highly Cited
2004
Highly Cited
2004
Sentiment classification on customer feedback data: noisy data, large feature vectors, and the role of linguistic analysis
We demonstrate that it is possible to perform automatic sentiment classification in the very noisy domain of customer feedback… 
Highly Cited
2002
Highly Cited
2002
Support Vector Clustering
We present a novel clustering method using the approach of support vector machines. Data points are mapped by means of a Gaussian… 
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
2000
Highly Cited
2000
Incremental and Decremental Support Vector Machine Learning
An on-line recursive algorithm for training support vector machines, one vector at a time, is presented. Adiabatic increments… 
Highly Cited
1999
Highly Cited
1999
Support Vector Method for Novelty Detection
Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset… 
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 (cid:12)nding a separating plane that discriminates… 
Highly Cited
1996
Highly Cited
1996
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… 
Review
1992
Review
1992
A survey of image registration techniques
Registration is a fundamental task in image processing used to match two or more pictures taken, for example, at different times… 
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