Search Results for "zend framework 3"

The recognition of Activities of Daily Living (ADL) has represented one of the most developed research areas in recent years. Its objective is to determine what daily activity is developed by the inhabitants of a smart environment. In this project, an ontology-based framework for the mining of ADL with a generic ontology and a modular architecture is proposed. The framework includes applications to: i) load multiple datasets available in literature, ii) to provide different methods for the...

Scene is a computer vision framework that performs background subtraction and object tracking, using two traditional algorithms and three more recent algorithms based on neural networks and fuzzy classification rules. For each detected object, Scene sends TUIO messages to one or several client applications. The present release features GPU accelerated versions of all the background subtraction methods and morphological post processing of the object blobs with dilation and erosion filters, implemented in OpenCL. ...

The Edlin toolkit provides a machine learning framework for linear models, designed to be easy to read and understand. The main goal is to provide an architecture and easy to edit working examples of implementations for popular learning algorithms.

LPCforSOS is a machine learning framework with a special focus on structured output spaces and pairwise learning. It supports currently multiclass, ordinal, hierarchical, multi-label and label ranking classification settings.

EpochX is an open source genetic programming framework, specifically for analysing the properties of evolutionary automatic programming. It supports 3 popular representations - Strongly-Typed GP, Context-Free Grammar GP and Grammatical Evolution.

A Machine Learning and Data Retrieval Framework

Neuroph OCR - Handwriting Recognition is developed to recognize hand written letter and characters. It's engine derived's from the Java Neural Network Framework - Neuroph and as such it can be used as a standalone project or a Neuroph plug in.

A graphical MatLab framework for estimating the parameters of, modeling and simulating static and dynamic linear and polynomial systems in the errors-in-variables context with the intent of comparing various estimation strategies.

Highly reusable and extensible Decision-Tree (Max-Gain) framework comprising of comprehensive input-processing and display functionality. Handles nominal, linear, continuous data. For preliminary description, refer - http://sushain.com/blog/archives/