Principal Component Analysis (PCA) has been widely used for dimensionality reduction in shape and appearance modeling. There have been several attempts of making PCA robust against outliers. However, there are cases in which a small subset of samples may appear as outliers and still correspond to plausible data. The example of shapes corresponding to fractures when building a vertebra shape mod...

We show how to efficiently project a vector onto the top principal components of a matrix, without explicitly computing these components. Specifically, we introduce an iterative algorithm that provably computes the projection using few calls to any black-box routine for ridge regression. By avoiding explicit principal component analysis (PCA), our algorithm is the first with no runtime dependen...

a survey on the abundance and diversity of fish larvae along the iranian waters of the oman sea, extending from hormuz strait to gowatr bay, was carried out in 2009 (before and post monsoon). fish larva were collected by a bongo net (300 µ mesh size) and temperature, salinity, dissolved oxygen, ph, chlorophyll-a, clarity, nitrate, nitrite, silicate and sulfate by oceanic data recorder (ctd) and...

Genetic  diversity  is  the  basis  of  the  natural  evolution  of  plant  breeding  and  biological  system  are  important  components  of  sustainability. The aim of this study was to evaluate 116 genotypes of Triticum turgidum from seven countries in terms of morphological traits. The results showed that high significant differences among the genotypes. The correlation between gra...

Principal component analysis (PCA) is often used for analyzing data in the most diverse areas. In this work, we report an integrated approach to several theoretical and practical aspects of PCA. We start by providing, intuitive accessible manner, basic principles underlying PCA its applications. Next, present a systematic, though no exclusive, survey some representative works illustrating poten...