Skip to search formSkip to main contentSkip to account menu

Principal component analysis

Known as: Principle components analysis, Principle Component Analysis, Probabilistic principal component analysis 
Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly… 
Wikipedia (opens in a new tab)

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2016
2016
In the area of computer vision and machine intelligence, image recognition is a prominent field. There have been several… 
2013
2013
There is an everyday increase of retinal images in different application such as human recognition and diagnosing the eye… 
2012
2012
A non-blind color image watermarking scheme using principle component analysis, discrete wavelet transform and singular value… 
Review
2011
Review
2011
— With the advancement of technology and easy availability of imaging tools, it’s not difficult now a days to manipulate digital… 
2009
2009
Summary Contour-based descriptors are among the main approaches in content based image retrieval. Most of these descriptors are… 
2008
2008
2002
2002
We develop a new signal modeling method, entropy-constrained adaptive PCA, that has the flexibility to accurately model the… 
1995
1995
Student display of regular physical activity has been presented as a principal component of the definition of a physically… 
1986
1986
Multiple components of magnetization were isolated in the natural remanent magnetiza- tion of samples of the Upper Devonian… 
Highly Cited
1981
Highly Cited
1981
A class of stable algorithms for adapting infinite impulse response (IIR) digital filters based on the concepts of nonlinear…