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The intention of this project is to give all serious users of the SNNS a place where they find a bugfix and patch management and where they get useful information about the SNNS.
This project provides a framework for testing and comparing different machine learning algorithms (particularly reinforcement learning methods) in different scenarios. Its intended area of application is in research and education.
A toolkit for the optical recognition of Psaltiki 19th century music notation. It is based on and requires the Gamera document image analysis framework (http://gamera.sf.net).
The Wikipedia Miner toolkit provides simplified access to Wikipedia. This open encyclopedia represents a vast, constantly evolving multilingual database of concepts and semantic relations; a promising resource for nlp and related research.
ESMERALDA is a development environment for statistical
recognizers operating on sequential data (speech, handwriting,
biological sequences). It supports continuous density Hidden
Markov models, Markov chain (N-gramm) models, and Gaussian
mixture models.
This project is being developed to be a Java based speech recognition (SR) program. In addition to the SR program itself, it includes a program which allows a user to view the sound being received by the computer. The user can manipulate this data.
CARMEN provides modular software for mobile robot control and navigation including: base and sensor control, obstacle avoidance, localization, path planning, people-tracking, and mapping. Language: C / Dependencies:gtk. See: http://carmen.sourceforge.net
This project aims to implement in java the following text mining techniques: Text Language Detection, Keywords and keyphrases extraction, Text Classification, Text Clustering, Single or multiple documents Summarization, Plagiarism Detection.
Algorithm::Evolutionary provides classes for performing simple evolutionary computation tasks, including definition of objects from XML and SOAP support. It should be interoperable with other EC libraries using SOAP.
DOGMA is a MATLAB toolbox for discriminative online learning. It implements all the state of the art algorithms in a unique and simple framework. Examples are Perceptron, Passive-Aggresive, ALMA, NORMA, SILK, Projectron, RBP, Banditron, etc.
This project is devoted to the creation of an open source Error-Correcting Output Codes (ECOC) library for the Machine Learning community. The ECOC framework is a powerful tool to deal with multi-class categorization problems.
MoMS (Model Management System) is a model management system for statistical models, a little bit like a database management system. Instead of having tables, we have models that can be updated and queried.
Web application to make user-friendly requests on large XML database.
Tools to XML-ize large bodies of semi-formal texts (like floras).
Computer-assisted specimen identification.
Uses natural language processing, 2D/3D images analysis and generation.
TextMarker is now developed and hosted at Apache UIMA (http://uima.apache.org/textmarker.html). TextMarker is a UIMA-based tool for information extraction and more. The full featured editor of the rule language and the build process of UIMA descriptors are complemented with components for visualization, explanation, testing and rule learning.
eBook Finder is an expert system designed to correctly identify the type of document you download from the internet. It currently supports pdf files, searches being made with Google Search.
SEMANTIXS is a semantic information extraction system that can extract, represent and visualize domain-specific information from free-text in the form of complex (and simple) relationships. Refer - http://www.cs.iastate.edu/~semantix/ for more info.
The sunflower library provides programming abstractions developed at the Autonomous Systems Lab http://www.asl.ethz.ch/. It contains a complete path planning and obstacle avoidance system, common mobile robotics tasks abstractions, and a 2D simulator.
This library is composed of two parts, a C++ library (developed under Linux) to manage a PDDL-like planner execution, problem file and output plan; and the connection to the Plexil Executive (the InterfaceAdapter class).
Compiler optimization for code that AI generates, reuses similar substrings of code to exponentially reduce the Big-O of compile. At runtime, CodeTree objects breed, rename vars, mutate code and run it instantly. For any realtime compilable language.