Search Results for "artificial intelligence python" - Page 11
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Showing 1303 open source projects for "artificial intelligence python"
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iCub is an open platform for scientists interested in investigating issues in embodied cognition. Here you find all the software and hardware documentation.
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Welsh Natural Language Toolkit
WNLT is a suite of open source natural language modules for the Welsh
The project supports the Welsh Language Technology domain with a set of NLP tools that drive innovation and advance the development of sophisticated textual analysis solutions. The WNLT project delivers four core NLP modules; a) Word Segmentation for separating text into words b) Sentence Boundary Disambiguation for finding sentence boundaries c) Part of Speech Tagger for determining the part of speech of each word d) Morphological Analyser for identifying the root form (lemma) of words.... -
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A broad collection of command-line-interface tools for performing machine learning operations. Each tool is a thin wrapper around functionality in a well-documented C++ class library. Waffles tools are designed to be simple, script-friendly, and to
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Part-of-speech tagging is the task of assigning symbols from a particular set to words in a natural language text. ACOPOST implements and extends well-known machine learning techniques and provides a uniform environment for testing.
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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,...
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jLDADMM
A Java package for the LDA and DMM topic models
The Java package jLDADMM is released to provide alternative choices for topic modeling on normal or short texts. It provides implementations of the Latent Dirichlet Allocation topic model and the one-topic-per-document Dirichlet Multinomial Mixture model (i.e. mixture of unigrams), using collapsed Gibbs sampling. In addition, jLDADMM supplies a document clustering evaluation to compare topic models. See the usage of jLDADMM in its website at http://jldadmm.sourceforge.net/ -
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libcrn is document image processing library written in C++11 for Linux, Windows, Mac OsX and Google Android. It is a toolbox that allows to create easily software such as OCRs and layout analysis tools.
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JABM is a Java framework for building agent-based simulation models using a discrete-event simulation framework.
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JASA allows researchers in agent-based computational economics to write high-performance trading simulations using a number of different auction protocols. The software also provides base classes for implementing simple adaptive trading agents.
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This is the Sourceforge reposository of the EU project Xperience. We work on developing a Cognitive Architecture for humanoid robots using a combination of developmental approaches and structural bootstrapping - a concept from language learning.
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openModeller is a complete C++ framework for species potential distribution modelling. The project also includes a graphical user interface, a web service interface and an API for Python.
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Java implementation of John Platt's Sequential Minimal optimization algorithm. This is an efficent Support Vector Machine solution.
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OPTSYS Framework Optimization Suite
Software Framework for Combinatorial Optimization using Metaheuristics
Die OPTSYS Framework Optimization Suite ist nicht nur eine Optimierungssoftware, sondern darüber hinaus ein umfangreiches Softwareframework für die kombinatorische Optimierung mit einem besonderen Fokus auf heuristische Lösungsmethoden. Das Framework versteht sich als Expertensystem zur Abbildung von kombinatorischen Optimierungsproblemen und für die Umsetzung, Anwendung und Evaluierung von zugehörigen Lösungsmethoden. Aufgrund der vielfältigen Funktionen zur Evaluation eignet es sich... -
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Virtual Eyewear
An eyewear trying simulator
Try this software and find out the eyewear style that is the most suitable for you. -
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graphnet
AI project using a graph technique on written text.
Experiments using a data sequencing technique on English language sentences. -
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ExSTraCS
Extended Supervised Tracking and Classifying System
This advanced machine learning algorithm is a Michigan-style learning classifier system (LCS) developed to specialize in classification, prediction, data mining, and knowledge discovery tasks. Michigan-style LCS algorithms constitute a unique class of algorithms that distribute learned patterns over a collaborative population of of individually interpretable IF:THEN rules, allowing them to flexibly and effectively describe complex and diverse problem spaces. ExSTraCS was primarily developed... -
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physicsmata
API for all possible cellular automata that work same at all angles
Its strange how the "sorted pointers" normalizing makes just about any random function, as long as it connects the inputs to the outputs on some path, vibrate as some nonlinear shape of wave. This could be used as a game interface for evolvable musical instruments or fluid puzzle games. Physicsmata is similar in effect to SmoothLife but simpler and pure Java. The cellular automata API takes a function to run at each point. Its parameters are sums of screen brightness (n color dimensions are... -
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HYBRYD
Library written in C with Python API for IPv6 networking
This project is a rewritten of an initial project that I've called GLUE and created in 2005. I'm trying to readapt it for Python 2.7.3 and GCC 4.6.3 The library has to be build as a simple Python extension using >python setup.py install and allows to create different kind of servers, clients or hybryds (clients-servers) over (TCP/UDP) using the Ipv6 Protocol. The architecture of the code is based on brain architecture. Will put an IPv6 adress active available as soon as... -
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The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.
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# ASPI Kit - Adaptive Identification and Control Software This software is under development by the ASPICC group. Its purpose is to allow users to learn and experiment the use of Neural Networks (NN's) and related Computational Intelligence algorithms on their own data. Users can upload their own data and experiment with various algorithms of various setups to see how the algorithms performs on their data. Users can also investigate and familiarize themselves with the Python code of the used algorithms.
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MARF is a general cross-platform framework with a collection of algorithms for audio (voice, speech, and sound) and natural language text analysis and recognition along with sample applications (identification, NLP, etc.) of its use, implemented in Java.
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FPF_predict
Fine Particle Fraction (FPF) predictor
Application implements models described by classical mathematical equation for in vitro deposition prediction based on characteristics of formulation and assay conditions. This work was funded by Poland-Singapore bilateral cooperation project no 2/3/POL-SIN/2012. Published article: https://www.dovepress.com/empirical-modeling-of-the-fine-particle-fraction-fornbspcarrier-based--peer-reviewed-fulltext-article-IJN -
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LightSpMV
lightweight GPU-based sparse matrix-vector multiplication (SpMV)
LightSpMV is a novel CUDA-compatible sparse matrix-vector multiplication (SpMv) algorithm using the standard compressed sparse row (CSR) storage format. We have evaluated LightSpMV using various sparse matrices and further compared it to the CSR-based SpMV subprograms in the state-of-the-art CUSP and cuSPARSE. Performance evaluation reveals that on a single Tesla K40c GPU, LightSpMV is superior to both CUSP and cuSPARSE, with a speedup of up to 2.60 and 2.63 over CUSP, and up to 1.93 and... -
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C++ template library for modular construction of factored probabilistic time-series models, model trainers, and recognizers.
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