Search Results for "engineering software" - Page 3
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Showing 74 open source projects for "engineering software"
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LBP in multiple platforms
LBP implementation in multiple computing platforms (ARM,GPU, DSP...)
The Local Binary Pattern (LBP) is a texture operator that is used in several different computer vision applications and implemented in a variety of platforms. When selecting a suitable LBP implementation platform, the specific application and its requirements in terms of performance, size, energy efficiency, cost and developing time has to be carefully considered. This is a software toolbox that collects software implementations of the Local Binary Pattern operator in several... -
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cognity
A neural network library for Java.
Cognity is an object-oriented neural network library for Java. It's goal is to provide easy-to-use, high level architecture for neural network computations along with reasonable performance. -
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mlpy
Machine Learning Python
mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. mlpy provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, clustering and feature selection. mlpy is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3. mlpy is available both for Python >=2.6 and Python 3.X. -
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Nen
neural network implementation in java
3-layer neural network for regression and classification with sigmoid activation function and command line interface similar to LibSVM. Quick Start: "java -jar nen.jar" -
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Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.
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SVM# is a svm(support vector machine) classification implemented in C#. The project contains both train and predict modules.
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BIL++ is a set of standalone C++ packages for data processing in Bioinformatics (Graph mining, Bayesian networks, Genetic algorithm, Discretization, Gene expression data analysis, Hypothesis testing).
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The Mars Rover Simulator project is based on the evolutionary robotics paradigm where an artificial agent acquires its skills through the process of artificial evolution. This simulator can be useful to evolve neural network controllers for the rover
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The aim of ALIVE is to develop new approaches to the engineering of flexible, adaptable distributed service-oriented systems based on the adaptation of social coordination and organisation mechanisms.
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Todbot is an AI addon to the gamestool virtual machine. The aim is to create an evolving neural network topology that should be capable of creating the optimal topology and network weighting to solve any problem given it.
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Yann is Yet Another Neural Network. Yann is a library to create fast neural networks. It is also a GUI to easily create, edit, train, execute and investigate networks. Multiple topologies, runtime properties and ensemble learning are supported.
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Este proyecto constituye una adaptacion y mejora del codigo ANFIS de dominio público de Roger Jang. / This project is an adaptation and improvement of the original public domain ANFIS code of Roger Jang.
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The STAIR Vision Library (SVL), originally developed to support the STanford AI Robot, provides software infrastructure for computer vision, machine learning, and probabilistic graphical models.
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Optex Analyzer is a software to analyze and compare algorithms to solve approximately optimization problems. It has a GUI that allows select a set of input files containing raw algorithm results. The analysis is shown with tables and charts.
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A java tool for anytime and interactive sequence mining. Aims at providing users with a way of analyzing her activity traces and extract activity schemes from them.
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A unique natural-language processing software, called Discovery, created on the CA Visual Objects/Vulcan.NET environment, which also has potential for effective "shallow approach" machine translation.
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This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
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Neural - is neural network engine with object-oriented design. Features: - Supports: backpropogation, RPROP algorithms. - Flexible input/outputs framework. - Distributed calculations.
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Blunder is an automated tool for analyzing chained exceptions in Java. It's usefull for classify, generate a customized error message and a list for possible solutions.
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Betelgeuse
Powerful machine learning modeling software suitable for industry use.
Betelgeuse is a machine learning modeling package designed to meet the requirements of heavy-duty industry use. It was designed to be efficient, reliable, and highly modular; it is developed primarily in Python to promote maintainability and rapid development, but uses Cython and C in critical bottlenecks for efficiency. It focuses on high-quality implementations of a diverse set of the most widely used machine learning algorithms. An important goal of Betelgeuse is to have a clean,... -
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pySPACE
Signal Processing and Classification Environment in Python using YAML
pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due... -
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qMaZda
Image analysis software
The open source project to port image analysis MaZda program to Linux and OS X platforms. See: http://www.eletel.p.lodz.pl/programy/mazda/ -
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Supertagger
Software for assigning supertags.
Supertagging is a process of statistical lexical disambiguation, preprocessing step to parsing, which assigns LTAG tree categories to the lexical items present in the input sentence. Thus, if the input sentence is in the form of a dependency tree, the task of the supertagger is to assign the most probable TAG family to each node and edge in the dependency tree.
