Search Results for "offline artificial intelligence\" - Page 8
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Showing 1225 open source projects for "offline artificial intelligence\"
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Brains is a generic plataform to construct arbitrarily complex artificial neural networks, allowing for parallelizide computing, inter-machine communication, on-flight configuration and on-flight control.
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Various planners, as released by planning researchers in the Planning, Agents and Intelligent Systems Group, Department of Informatics, King's College London. These include OPTIC, POPF, COLIN, CRIKEY3, LPRPG, Marvin and TSGP.
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Virtual Laboratory Environment
A multi-modeling and simulation environment to study complex systems
VLE is a multi-modeling and simulation environment to study complex dynamic systems. VLE is based on the discrete event specification DEVS. and it implements the DSDE formalism (A merge of Dynamic Structure DEVS, DSDEVS, with Parallel DEVS, PDEVS). VLE provides a complete set of C++ libraries, called VFL (VLE Foundation Libraries), to develop DEVS models, to gets results of simulations, to launch simulation on cluster. The models can be developed with the DEVS formalism or with the classical... -
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SLING
A natural language frame semantics parser
The aim of the SLING project is to learn to read and understand Wikipedia articles in many languages for the purpose of knowledge base completion, e.g. adding facts mentioned in Wikipedia (and other sources) to the Wikidata knowledge base. We use frame semantics as a common representation for both knowledge representation and document annotation. The SLING parser can be trained to produce frame semantic representations of text directly without any explicit intervening linguistic... -
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Presage
the intelligent predictive text entry platform
Presage (formerly Soothsayer) is an intelligent predictive text entry system. Presage generates predictions by modelling natural language as a combination of redundant information sources. Presage computes probabilities for words which are most likely to be entered next by merging predictions generated by the different predictive algorithms. Presage's modular and extensible architecture allows its language model to be extended and customized to utilize statistical, syntactic, and semantic... -
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Simultra
Multiagent simulator of road traffic in Qt/C++ and OpenStreetMap.
Simultra is an open-source, hybrid road traffic simulator designed to handle large roadmaps in real-time. It combines microscopic and mesoscopic simulations into one multiagent hybrid simulator. The large-scale maps are modelled mesoscopically in real-time, and the complex traffic interactions benefit from detailed agent-based microscopic simulations. To resolve the concurrency issues within the maps representation and the meso-micro transitions, Simultra combines an event-based mesoscopic... -
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PyTom
http://www.sciencedirect.com/science/article/pii/S1047847711003492
PyTom is a toolbox developed for interpreting cryo electron tomography data. All steps from reconstruction, localization, alignment and classification are covered with standard and improved methods. Please sign up to our mailing list to keep up with the most recent updates and versions. -
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Tensor Comprehensions
A domain specific language to express machine learning workloads
Tensor Comprehensions (TC) is a fully functional C++ library that automatically synthesizes high-performance machine learning kernels using Halide, ISL, and NVRTC or LLVM. TC additionally provides basic integration with Caffe2 and PyTorch. We provide more details in our paper on arXiv. This library is designed to be highly portable, machine-learning-framework agnostic and only requires a simple tensor library with memory allocation, offloading, and synchronization capabilities. -
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Boon Rules
Study the computational basis of human learning and inference
The main problem of the machine learning is to find a scientific regularity in experimental observations. Many methods may be served - from baseless guesses to an accurate investigation of models - to create a possible scientific interpretation. This approach consider on searching for underlying laws. Laws can be evoked from the massive data sets (genetics, robot sensors, social networks, adverisement) available now (so called the Big Data). -
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TorchCraft
Connecting Torch to StarCraft
We present TorchCraft, a library that enables deep learning research on Real-Time Strategy (RTS) games such as StarCraft: Brood War, by making it easier to control these games from a machine learning framework, here Torch. This white paper argues for using RTS games as a benchmark for AI research, and describes the design and components of TorchCraft. TorchCraft is a BWAPI module that sends StarCraft data out over a ZMQ connection. This lets you parse StarCraft data and interact with BWAPI... -
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Caffe Framework
Caffe, a fast open framework for deep learning
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine... -
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kcws
Deep Learning Chinese Word Segment
Deep learning chinese word segment. Install the bazel code construction tool and install tensorflow (currently this project requires tf 1.0.0alpha version or above) Switch to the code directory of this project and run ./configure. Compile background service. Pay attention to the public account of waiting for words and reply to kcws to get the corpus download address. Extract the corpus to a directory. Change to the code directory.After installing tensorflow, switch to the kcws code... -
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VideoMan Library
C++ library for image acquisition and visualization
Library for capturing video from cameras, 3d sensors, frame-grabbers, video files and image sequences. It can also display multiple images using OpenGL with different layouts. Easy integration with OpenCV, CUDA... Perfect for computer vision. Keywords: video capture, computer vision, machine vision, opencv, opengl, cameras, video input devices, firewire, usb, gige -
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Madara
Middleware for distributed applications
The purpose of the project is to develop a portable programming framework that facilitates distributed and multi-threaded programming for C++, Java, and Python. MADARA was originally developed as an agent-based middleware specifically for real-time, distributed artificial intelligence, but is now more general purpose for distributed timing, control, knowledge and reasoning, and quality-of-service. MADARA is composed of several tools and middleware, and the main entry point into the system... -
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perkun2
experimental AI language for multiple agents
An experimental AI language. Attempts to maximize the expected value of the payoff function by appropriate choosing the actions (output variables values). It supports multiple agents performing the actions interchangeably. This project does not work properly. I leave it here only for reference. -
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NOMAD is a C++ code that implements the MADS algorithm (Mesh Adaptive Direct Search) for difficult blackbox optimization problems. Such problems occur when the functions to optimize are costly computer simulations with no derivatives.
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2D Statistical Models. Building: shape model, texture model and concatenated appearance model; Fitting: 1D profile ASM, 2D profile ASM, direct local texture constrained(LTC) ASM, basic AAM, ICIA AAM, IAIA AAM, etc.
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UnrealCV
Connecting Computer Vision to Unreal Engine
UnrealCV is a project to help computer vision researchers build virtual worlds using Unreal Engine (UE). It extends UE with a plugin. UnrealCV can be used in two ways. The first one is using a compiled game binary with UnrealCV embedded. This is as simple as running a game, no knowledge of Unreal Engine is required. The second is installing the UnrealCV plugin into Unreal Engine and using the editor to build a new virtual world. -
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NNVM
Open deep learning compiler stack for cpu, gpu
The vision of the Apache NNVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging machine learning models for any hardware platform. Compilation of deep learning models into minimum deployable modules. Infrastructure to automatically generates and optimize models on more backend with better performance.... -
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OpenPR stands for Open Pattern Recognition project and is intended to be an open source library for algorithms of image processing, computer vision, natural language processing, pattern recognition, machine learning and the related fields.
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PLaTHEA
People Localization and Tracking for HomE Automation
PLaTHEA is a stereo vision based indoor localization and tracking system. The system acquires a stereo video stream from different kind of input devices included not-synchronized network cameras. An usage tutorial for an older is provided at http://www.dis.uniroma1.it/~leotta/demos/plathea/plathea.html. If you want to use this code please cite the research paper at https://onlinelibrary.wiley.com/doi/abs/10.1002/spe.2262. -
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JuliusModels
Open source speech models for Julius in English and other languages.
Open source speech models for Julius speech decoder. Its aim is to give access a wider community of speech recognition enthusiasts to quality models, which they can use in their own projects on different OS platforms (Unix, Windows, etc...) All of the models are based on HTK modelling software and data sets available freely on the Internet. -
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The Edge Machine Learning library
Machine learning algorithms for edge devices
... of magnitude lower than other modern ML algorithms. The trained models can be loaded onto edge devices such as IoT devices/sensors, and used to make fast and accurate predictions completely offline. A tool that adapts models trained by above algorithms to be inferred by fixed point arithmetic. -
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NIVEL9
Programa para crear y ejecutar Sistemas Expertos
NIVEL9 es el nombre del software informático diseñado por el Ing. Mauricio Ernesto Alfaro, el cual se basa en las teorías de Inteligencia Artificial, específicamente de Sistemas Expertos. NIVEL9 entra en la categoría de "caparazón para sistema experto" o mejor conocido en inglés como "Expert System Shell": es decir un software para crear diferentes Sistemas Expertos y ejecutarlos dentro del mismo software. NIVEL9 nació como un proyecto para apoyar al Instituto de Ciencias del Mar y...