18 projects tagged "Artificial Intelligence"
Updated 24 Apr 2013
Critterding
| Pop | 237.62 |
|---|---|
| Vit | 29.70 |
Critterding is a "Petri dish" universe in 3D that demonstrates evolving artificial life. Critters start out with completely random brains and bodies, but will automatically start evolving into something with much better survival skills.
Updated 28 Dec 2009
NNF2
| Pop | 145.17 |
|---|---|
| Vit | 3.10 |
NNF2 is a C++ library for feed-forward neural networks (also called multi-layer perceptrons). Its modular design makes it easily extensible by users. Batch training and saving of networks are supported.
Updated 27 Oct 2005
JFDraw
| Pop | 130.87 |
|---|---|
| Vit | 4.02 |
JFDraw is a Java vector graphics drawing application and library package. It is focused on vector graph drawing field. It is useful for mechanical, electronic, architectural graph drawing applications, or even business process or workflow graphs.
Updated 07 Jun 2008
Neural Network Framework
| Pop | 91.71 |
|---|---|
| Vit | 5.07 |
Neural Network Framework is a C++ framework to develop, simulate, and analyze arbitrary complex neural networks. The programmer can use the classes provided to create neural networks with arbitrary topology and mixed type of neurons. It's very easy to add customized neurons and layers.
Updated 18 May 2010
Neuroph Framework
| Pop | 90.83 |
|---|---|
| Vit | 2.89 |
Neuroph is lightweight Java Neural Network Framework that can be used to simulate common neural network architectures. With a small number of basic classes that correspond to basic NN concepts, it is easy to learn. It also has a nice GUI application.
Updated 08 Oct 2003
LinkGrammar-WN
| Pop | 63.09 |
|---|---|
| Vit | 1.00 |
LinkGrammar-WN is a lexicon expansion for the Link Grammar Parser. The Link Grammar Parser is a syntactic parser of the English language that is capable of handling a wide variety of syntactic constructions and is considered quite robust. The LinkGrammar-WN project aims to import lexical information from WordNet in an effort to increase the size of the LGP lexicon. This project is of interest to anyone interested in NLP (natural language parsing) of English text.
Updated 01 Oct 2003
OMCSNet-WordNet
| Pop | 60.75 |
|---|---|
| Vit | 2.00 |
The OMCSNet-WordNet project aims to improve the quality of the OMCSNet dataset by using automated processes to map WordNet synonym sets to OMCSNet concepts and import additional semantic linkage data from WordNet. It is based on OMCSNet 1.2, a semantic network and inference toolkit written in Python/Java. OMCSNet currently contains over 280,000 separate pieces of common sense information extracted from the raw OMCS dataset. This project is also based on WordNet, an online lexical reference system that in recent years has become a popular tool for AI researchers.
Updated 26 Jan 2004
OMCSNetCPP
| Pop | 59.41 |
|---|---|
| Vit | 1.77 |
OMCSNetCPP is a C++ API and inference toolkit for accessing OMCSNet, a semantic network mined out of the Open Mind Common Sense knowledge base. The goal of this project is to provide a class library that allows programmers to easily add common sense reasoning capabilities to C++ applications.
Updated 25 Feb 2008
BinarySEC
| Pop | 50.20 |
|---|---|
| Vit | 2.49 |
BinarySEC is an intelligent Web application firewall designed to suppress malicious traffic on Web sites and applications. Its artificial intelligence engine learns normal traffic and blocks malicious requests with very high accuracy. BinarySEC secures against a wide range of attacks, including cross-site scripting (XSS), SQL injection, command injection, PHP includes, parameter tampering, buffer overflow, directory traversal, attack obfuscation, and more. BinarySEC for Apache includes a graphical installer and a Web-based administration interface.
Updated 25 Oct 2011
GEneral NEural SImulation System
| Pop | 47.56 |
|---|---|
| Vit | 4.62 |
GENESIS (short for GEneral NEural SImulation System) is a general purpose simulation platform that was developed to support the simulation of neural systems ranging from subcellular components and biochemical reactions to complex models of single neurons, simulations of large networks, and systems-level models. It was developed as a research tool to provide a standard and flexible means for constructing structurally realistic models of biological neural systems.
