Search Results for "neural net" - Page 3
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Showing 72 open source projects for "neural net"
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FANNshell is a command-line wrapper for the FANN (Fast Artificial Neural Net) library. It provides an easy way to create, train, test, import, and export FANN neural nets via the shell.
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Simulation of plants, prey, and predators, using sense->think->action paradigm with neural net processing. Reproduction and mutation implemented.
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‘intelliworm’ is a prototype simulation of a Intelligent Species of a common earth worm,which inherits human like decision making capabilities through Neural Network intelligence representation,all developed by integrating .NET with Lisp and Yacc.
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AKIRA aims to create a C++ development framework to build cognitive architectures and complex artificial intelligent agents.Features:KQML,Fuzzy Logic,Neural Net,Fuzzy Cognitive Maps and DIPRA (a distributed BDI - Belief Desire Intention goals model)
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The aim of GUINNEA (Graphical User Interfaced Neural Network Architecture) is to develop a comfortable and high-featured neural net simulator which is highly configurable and flexible. It will support many neural nets and visualization features for those
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NxNet is an implementation of a BPN neural network written in C#. NxNet allows the user to configure the neural net, train and query the trained net. NxNet 2.0 introduces a batch query capability. Requires .Net Framework 2.0 be installed also.
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A neural net module written in python. The aim of the project is to provide a large set of neural network types accessed by an API that is easy to use and powerful.
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All-in-One Payroll and HR PlatformWe design our technology to make workforce management easier. APS offers core HR, payroll, benefits administration, attendance, recruiting, employee onboarding, and more.
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Jannis stands for "J Artificial Neural Net Interactive Simulator". Jannis' primary purpose is simulation of neural net models for scientific experiments in special-needs-education and neuropsychology.
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neuralnetgen is intended to be a universal neural net generator that receives a neural net description (on Neural Net Description Language, also developed on this project) and generates ANSI C code of a library that implements it.
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Net.py is a tool for learning about neural nets. Currently, it only allows the user to experiment with a Hopfield net. I am now extending it to cover the Kohonen net. I'd be pleased to receive suggestions and criticism.
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DANNU - Database Artificial Neural Network Utility. A C#/.NET utility implementing the "NeuroBox" library which allows the user to import data from a database and train a network with it. A fully featured NN utlitility is envisioned.
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Program to detect human faces on a digital picture. It uses a MLP neural net that receive relative distances from face distribution clusters of the image space. Written in C++. Requires newmat and libann libraries.
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Fingerprint Imaging Software -- fingerprint pattern classification, minutae detection, Wavelet Scalar Quantization(wsq) compression, ANSI/NIST-ITL 1-2000 reference implementation, baseline and lossless jpeg, image utilities, math and MLP neural net libs
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The intention of this project is to create a structure for future, larger neural net designs, to create a symmetric multi-processing neural network, capable of sustaining a large amount of simulated neurons. Note: this description does not necessarily s
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DLA-Sign-Language
Convolutional neural net model for sign language pictures
Convolutional neural net model for the dla sign language mnist data set -
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A Visual Studio .NET C++ application can perform machine learning using genetic algorithm, naive bayes, KNN, and Artificial Neural Networks (ANNs) read and processed from any standard ARFF.
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ScienceNET is a open source library written in C# which aims to provide a self contained clean .NET framework for neural networks, genetic algorithms, optimization, image processing and for other domains of a computational science.
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GHAPACK is a suite of tools around the Generalized Hebbian Algorithm. The Generalized Hebbian Algorithm (GHA) is a neural-net-like algorithm that allows the eigen decomposition of a dataset to be "learned" from serially-presented data.