On Transformations of Random Vectors

Introducing a method for extracting features from facial images based on applying transformations to features obtained from convolutional neural networks

In pattern recognition, features are denoting some measurable characteristics of an observed phenomenon and feature extraction is the procedure of measuring these characteristics. A set of features can be expressed by a feature vector which is used as the input data of a system. An efficient feature extraction method can improve the performance of a machine learning system such as face recognit...

Autoregressive Gaussian Random Vectors of First Order

Estimation of Spectral Measure of Stable Random Vectors

This article has no abstract.

Projection correlation between two random vectors.

We propose the use of projection correlation to characterize dependence between two random vectors. Projection correlation has several appealing properties. It equals zero if and only if the two random vectors are independent, it is not sensitive to the dimensions of the two random vectors, it is invariant with respect to the group of orthogonal transformations, and its estimation is free of tu...

SEIMCHA: a new semantic image CAPTCHA using geometric transformations

As protection of web applications are getting more and more important every day, CAPTCHAs are facing booming attention both by users and designers. Nowadays, it is well accepted that using visual concepts enhance security and usability of CAPTCHAs. There exist few major different ideas for designing image CAPTCHAs. Some methods apply a set of modifications such as rotations to the original imag...