Showing 5 open source projects for "image analysis algorithm"

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  • 1
    ML.NET

    ML.NET

    Open source and cross-platform machine learning framework for .NET

    With ML.NET, you can create custom ML models using C# or F# without having to leave the .NET ecosystem. ML.NET lets you re-use all the knowledge, skills, code, and libraries you already have as a .NET developer so that you can easily integrate machine learning into your web, mobile, desktop, games, and IoT apps. ML.NET offers Model Builder (a simple UI tool) and ML.NET CLI to make it super easy to build custom ML Models. These tools use Automated ML (AutoML), a cutting edge technology that...
    Downloads: 13 This Week
    Last Update:
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  • 2

    Tsf_Mdnnhn

    Time Series Forecasting.

    Implementation of algorithm allowing Time Series Forecasting.
    Downloads: 0 This Week
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  • 3
    Accord.NET Framework

    Accord.NET Framework

    Scientific computing, machine learning and computer vision for .NET

    The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono.
    Downloads: 9 This Week
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  • 4
    neural network designer

    neural network designer

    a dbms for neural nets. Chatbots, DTrees, random forests, n-grams,...

    ...With the designer, you are able to create different types of decision trees, random forests, n-grams, pattern-matchers, conversational agents and all sorts of AI related algorithms. You can combine statistical approaches as well as pattern matchers or others. Do natural language processing, image or data analysis & interpretation,...
    Downloads: 8 This Week
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  • 5
    CRFSharp

    CRFSharp

    CRFSharp is a .NET(C#) implementation of Conditional Random Field

    CRFSharp(aka CRF#) is a .NET(C#) implementation of Conditional Random Fields, an machine learning algorithm for learning from labeled sequences of examples. It is widely used in Natural Language Process (NLP) tasks, for example: word breaker, postagging, named entity recognized, query chunking and so on. CRF#'s mainly algorithm is the same as CRF++ written by Taku Kudo. It encodes model parameters by L-BFGS. Moreover, it has many significant improvement than CRF++, such as totally...
    Downloads: 0 This Week
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