Search Results for "principal component analysis"

MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack

This code uses a technique originally developed for facial recognition to describe shear stress distributions in open channel flow. In this approach, a synthetic database of images representing normalized shear stress distributions is formed from the training data set using recurrence plot analysis. A face recognition algorithm is then employed to synthesize the recurrence plots and transform the original database into short-dimension vectors containing similarity weights proportional to the principal components of the distribution of images. These vectors capture the intrinsic properties of the boundary shear stress distribution of the cases in the training set, and are sensitive to variations of the corresponding hydraulic parameters. ...

PlexBench is a cross-platform, web-enabled, analysis tool that is driven by a scalable backpropagation feed-forward neural network. It uses embedded Perl for scripting and is written in the style of an in-process Component Object Model (COM) C++ program.

This project aims at developing a face authentication system, using the Eigenfaces, and Eigenfeatures. The Approach is a principal component analysis method, in which a set of characteristic pictures are used to describe the variation between face images.