Showing 19 open source projects for "framework-arduinoststm32"

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  • 1
    Dshell

    Dshell

    Dshell is a network forensic analysis framework

    An extensible network forensic analysis framework. Enables rapid development of plugins to support the dissection of network packet captures. This is a major framework update to Dshell. Plugins written for the previous version are not compatible with this version, and vice versa. By extension, dpkt and pypcap have been replaced with Python3-friendly pypacker and pcapy (respectively).
    Downloads: 0 This Week
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  • 2
    Uranie

    Uranie

    Uranie is CEA's uncertainty analysis platform, based on ROOT

    Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. ...
    Downloads: 2 This Week
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  • 3
    StreamAlert

    StreamAlert

    StreamAlert is a serverless, realtime data analysis framework

    StreamAlert is a serverless, real-time data analysis framework that empowers you to ingest, analyze, and alert on data from any environment, using data sources and alerting logic you define. Computer security teams use StreamAlert to scan terabytes of log data every day for incident detection and response. Incoming log data will be classified and processed by the rules engine. Alerts are then sent to one or more outputs.
    Downloads: 0 This Week
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  • 4
    Gamera is a framework for the creation of structured document analysis applications by domain experts. It combines a programming library with GUI tools for the training and interactive development of recognition systems.
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  • 5
    Modular toolkit for Data Processing MDP
    The Modular toolkit for Data Processing (MDP) is a Python data processing framework. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. From the scientific developer's perspective, MDP is a modular framework, which can easily be expanded.
    Downloads: 0 This Week
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  • 6
    scipion-xmipp

    scipion-xmipp

    Image processing framework to integrate EM software packages.

    Scipion is an image processing framework to obtain 3D models of macromolecular complexes using Electron Microscopy (3DEM). It integrates several software packages and presents an unified interface for both biologists and developers. Scipion allows to execute workflows combining different software tools, while taking care of formats and conversions. Additionally, all steps are tracked and can be reproduced later on.
    Downloads: 0 This Week
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  • 7
    Pyphant is a framework for scientific data analysis. It features a flexible plugin architecture allowing for the application in many different fields. For the analysis a graph of processing steps is constructed, that can be applied via the cli as well.
    Downloads: 0 This Week
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  • 8
    BRAHMS is a Modular Execution Framework for dynamical systems. It knits together independently-authored software modules implementing dynamical processes into an integrated system, and supervises the deployment and execution of that system.
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  • 9
    A web-based interface for the Hadoop MapReduce framework that simplifies the process of writing and running MapReduce jobs. Aimed at introducing parallelism concepts in introductory computer science courses.
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  • 10
    JBoost is a simple, robust system for classification. JBoost contains implementations of several boosting algorithms in an alternating decision tree framework. In addition, JBoost provides extensible software for adding more learning algorithms.
    Downloads: 0 This Week
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  • 11
    Graph-based Extraction and Summarization - a generic graph-based summarization framework. Basic functionality is provided - third-party modules can be plugged in.
    Downloads: 0 This Week
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  • 12
    A framework to support the developpement of trace based applications
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  • 13
    Python framework for video processing and content analysis using CUDA for acceleration.
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  • 14
    A lightweight, browsing-based, 100% Python, federated data integration framework. Users may create custom schemas for disparate sources, query and expand results across sources to find related data; for use in fields such as bioinformatics and datamining
    Downloads: 0 This Week
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  • 15
    Using this plugin-based framework, you can instantly start working on the *brain* of your bot (irc bot, chatterbot, robot, ...). With support for db, irc, logging and programming-language independent plugins, users can easily enhance the functionality.
    Downloads: 1 This Week
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  • 16
    Poor Man's HPC is a framework that allows distributing and running code on a server farm. pmHPC is a scaled down and simplified version of distributed computing projects such as SETI, so is a perfect fit for enthusiasts and universities.
    Downloads: 0 This Week
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  • 17
    minITIL is an open source implementation intended to create a solid framework for building applications needed in real life deployments of Information Technology services based on ITIL framework.
    Downloads: 0 This Week
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  • 18
    A configurable knowledge management framework. It works out of the box, but it's meant mainly as a framework to build complex information retrieval and analysis systems. The 3 major components: Crawler, Analyzer and Indexer can also be used separately.
    Downloads: 0 This Week
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  • 19
    ExoPlanet

    ExoPlanet

    GUI based toolkit for running common Machine Learning algorithms.

    ExoPlanet provides a graphical interface for the construction, evaluation and application of a Machine Learning model in predictive analysis. With the back-end built using the numpy and scikit-learn libraries, as a toolkit, ExoPlanet couples fast and well tested algorithms, a UI designed over the Qt4 framework, and graphs rendered using Matplotlib to provide the user with a rich interface, rapid analytics and interactive visuals. ExoPlanet is designed to have a minimal learning curve, allowing researchers to focus on the applicative aspect of Machine Learning rather than their implementation details. It provides algorithms for unsupervised and supervised learning, which may be done with continuous or discrete labels. ...
    Downloads: 0 This Week
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