Showing 15 open source projects for "learning vector quantization"

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  • 1
    JAX

    JAX

    Composable transformations of Python+NumPy programs

    With its updated version of Autograd, JAX can automatically differentiate native Python and NumPy functions. It can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation) via grad as well as forward-mode differentiation, and the two can be composed arbitrarily to any order. What’s new is that JAX uses XLA to compile and run your NumPy programs on GPUs and...
    Downloads: 0 This Week
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  • 2
    SMILI

    SMILI

    Scientific Visualisation Made Easy

    The Simple Medical Imaging Library Interface (SMILI), pronounced 'smilie', is an open-source, light-weight and easy-to-use medical imaging viewer and library for all major operating systems. The main sMILX application features for viewing n-D images, vector images, DICOMs, anonymizing, shape analysis and models/surfaces with easy drag and drop functions. It also features a number of standard processing algorithms for smoothing, thresholding, masking etc. images and models, both with...
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    Downloads: 5 This Week
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  • 3
    geocompr

    geocompr

    Geocomputation with R: an open source book

    This repository hosts the source for Geocomputation with R, an open-source book covering spatial data analysis, visualization, and modeling using R. It teaches how to work with vector and raster data, coordinate systems, mapping, and geocomputation techniques using packages like sf, terra, tmap, and more. Actively maintained and updated for real-world geospatial workflows.
    Downloads: 2 This Week
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  • 4
    Phenalysis

    Phenalysis

    Analyze agronomic plant research plots in aerial orthomosaic images.

    A graphical user interface to import, analyze and export plots from orthomosaic images of agronomic trials. Please cite the following reference in your work if you use Phenalysis: Khan Z and Miklavcic SJ (2019) An Automatic Field Plot Extraction Method From Aerial Orthomosaic Images. Front. Plant Sci. 10:683. doi: https://doi.org/10.3389/fpls.2019.00683 This tool is being developed through the sponsorship of the Australian Research Council's Industrial Transformation Research Hub on...
    Downloads: 0 This Week
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  • 5

    VecText

    Converting text to a structured representation

    VecText is an application that converts raw text to a structured format suitable for various data mining software. The application is written in interpreted programming language Perl. A part of the functionality is realized by external modules (e.g., Lingua::Stem::Snowball for stemming). The graphical user interface enables user-friendly software employment without requiring specialized technical skills and knowledge of a particular programming language, names of libraries and their...
    Downloads: 0 This Week
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  • 6
    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: 2 This Week
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  • 7

    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...
    Downloads: 0 This Week
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  • 8

    libVMR

    VMR - machine learning library

    libVMR is a class library written in Java which implements code generator for group method of data handling - GMDH. The library is intended for users, with machine learning skills. libVMR provides an effective framework for the research and development of data mining and predictive analytics. libVMR is based on the most popular neural network model with a higher generalization ability from kernel tricks - vector machine by Reshetov (VMR). The library has been designed to learn from data sets. ...
    Downloads: 0 This Week
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  • 9
    NOTE: This project was moved to: https://github.com/eetorres The MSMVTL is an easy to use Matrix and Vector template implementation for people who is learning numerical or simulation programming.
    Downloads: 0 This Week
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  • 10

    lonestar

    A feature selection and classification algorithm based on L1 Norm SVM

    A feature selection and classification algorithm. It is based on L1 Norm Support Vector Machine with t-test and Recursive Feature Elimination.
    Downloads: 0 This Week
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  • 11
    ssSVMToolbox is a Java application capable of performing supervised and semi-supervised learning tasks with Support Vector Machines. It is based on Spring (http://springframework.org/), RapidMiner (http://www.rapidminer.com) and Eclipse RCP (http://eclip
    Downloads: 0 This Week
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  • 12
    SVM# is a svm(support vector machine) classification implemented in C#. The project contains both train and predict modules.
    Downloads: 0 This Week
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  • 13
    This project implements the parallelized version of the LBG vector quantization algorithm on Cell Broadband Engine.
    Downloads: 0 This Week
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  • 14
    libit provides easy to use yet efficient tools for C for signal processing, coding, or scientific code in general. It includes basic vector, matrix and function types, some common source and channel coding tools such as quantization, entropy coding, etc.
    Downloads: 0 This Week
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  • 15
    Ruby SVM is a Ruby binding to the very popular and highly useful libsvm library (released under a seperate license) This allows you to effortlessly experiment with machine learning, in particular Support Vector Machines, in Ruby. SVM's have found use in
    Downloads: 0 This Week
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