Showing 50 open source projects for "c code compiler"

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  • 1
    nGraph

    nGraph

    nGraph has moved to OpenVINO

    Frameworks using nGraph Compiler stack to execute workloads have shown up to 45X performance boost when compared to native framework implementations. We've also seen performance boosts running workloads that are not included on the list of Validated workloads, thanks to nGraph's powerful subgraph pattern matching. Additionally, we have integrated nGraph with PlaidML to provide deep learning performance acceleration on Intel, nVidia, & AMD GPUs. nGraph Compiler aims to accelerate developing...
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  • 2
    GAAS

    GAAS

    Autonomous aviation intelligence software for drones and VTOL

    GAAS (Generalized Autonomy Aviation System) is an open source software platform for autonomous drones and VTOLs. GAAS was built to provide a common infrastructure for computer-vision based drone intelligence. In the long term, GAAS aims to accelerate the coming of autonomous VTOLs. Being a BSD-licensed product, GAAS makes it easy for enterprises, researches, and drone enthusiasts to modify the code to suit specific use cases. Our long-term vision is to implement GAAS in autonomous passenger...
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  • 3
    xLearn

    xLearn

    High performance, easy-to-use, and scalable machine learning (ML)

    xLearn is a high-performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM), all of which can be used to solve large-scale machine learning problems. xLearn is especially useful for solving machine learning problems on large-scale sparse data. Many real-world datasets deal with high dimensional sparse feature vectors like a recommendation system where the number of categories and...
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  • 4
    SLING

    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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  • 5
    Caffe Framework

    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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  • 6
    kcws

    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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  • 7
    EasyPR

    EasyPR

    An easy, flexible, and accurate plate recognition project

    EasyPR is an open-source license plate recognition system designed to detect and recognize vehicle license plates from images using computer vision and machine learning techniques. The project focuses primarily on recognizing Chinese license plates but also demonstrates general approaches to automatic number plate recognition systems. Built on top of the OpenCV computer vision library, EasyPR provides algorithms for detecting license plate regions in images, segmenting characters, and...
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  • 8
    NNVM

    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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  • 9
    Caffe

    Caffe

    A fast open framework for deep learning

    Caffe is an open source deep learning framework that’s focused on expression, speed and modularity. It’s got an expressive architecture that encourages application and innovation, and extensible code that’s great for active development. Caffe also offers great speed, capable of processing over 60M images per day with a single NVIDIA K40 GPU. It’s arguably one of the fastest convnet implementations around. Caffe is developed by the Berkeley AI Research (BAIR)/The Berkeley Vision and...
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  • 10
    Multiple Back-Propagation (with CUDA)

    Multiple Back-Propagation (with CUDA)

    Open source software for training neural networks

    Multiple Back-Propagation is an open source software application for training neural networks with the backpropagation and the multiple back propagation algorithms. Currently this project is also hosted at http://code.google.com/p/multiplebackpropagation
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  • 11
    tiny-dnn

    tiny-dnn

    header only, dependency-free deep learning framework in C++14

    tiny-dnn is a C++14 implementation of deep learning. It is suitable for deep learning on limited computational resources, embedded systems, and IoT devices.
    Downloads: 1 This Week
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  • 12

    LightSpeedANN

    Generator for optimized, vectorized neural net code

    This Ruby program takes in a topology specification for an artificial neural network and emits optimized C code (using SSE intrinsics) that implements fast forward and backward propagation for that specific topology.
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  • 13

    Automatic cell lineage reconstruction

    Automatic segmentation and tracking for 3D time-lapse microscopy

    From Amat et al., Nature Methods, 2014*: "The comprehensive reconstruction of cell lineages in complex multicellular organisms is a central goal of developmental biology. We present an open-source computational framework for segmentation and tracking of cell nuclei with high accuracy and speed. We demonstrate its (1) generality, by reconstructing cell lineages in four-dimensional, terabyte-sized image data of fruit-fly, zebrafish and mouse embryos, acquired with three different types of...
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  • 14

    KMeansAniX

    Animation of kmeans clustering using X Window System

    Open source animation of kmeans clustering in X Window System using the C++ libplotter library. Supports Linux, Mac, and BSD. Includes common initialization methods such as Forgy, Macqueen, random, and angular. Sample videos are available through the Files Tab above. The SVN repo is accessible thorugh the Code Tab above. Requires a C++ compiler, libplot-dev, and libncurses5-dev Mac alternative to libplot-dev: macports plotutils +x11
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  • 15

    Genetic Algorithms Engine - Blackjack

    A genetic algortihm engine that evolves blackjack basic strategy.

    ...To see it in action, download the zip file and run either: GABlackjack_Demo.exe     (quick)   or GABlackjack_Long.exe       (slow, but it achieves better results). The code was written in C++, using MS Visual Studio 6.0 and MS Visual Source Safe 6.0. The genetic algorithm engine supports various mutation rates, ranked parental selection, stochastic sampling parental selection, cyclic crossover, crossover at each gene, cloning the best individual each generation, and creating random individuals each generation. ...
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  • 16

    drvq

    dimensionality-recursive vector quantization

    ...A detailed README file describes the usage of the software, including license, requirements, installation, file formats, sample data, tools, and options. With the sample data provided and the default options, it is possible to test the code immediately as a demo. DRVQ has a 2-clause BSD license. Please refer to the DRVQ software home page, the research project, or the original publication for more information. The latest code is available at github.
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  • 17
    cCNN

    cCNN

    A fast implementation of LeCun's convolutional neural network

    Code of this library is partialy based on myCNN MATLAB class written by Nikolay Chemurin.
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  • 18

    LBP in multiple platforms

    LBP implementation in multiple computing platforms (ARM,GPU, DSP...)

    ...This is a software toolbox that collects software implementations of the Local Binary Pattern operator in several platforms: - OpenCL for CPU & GPU - OpenCL for GPU (branchless) - C code optimized for ARM - OpenGL ES 2.0 shaders mobile GPUs - C code for TI C64x DSP core (branchless) - C code for TTA processor synthesis If you use the code somewhere, please cite: Bordallo López M., Nieto A., Boutellier J., Hannuksela J., and Silvén O. "Evaluation of real-time LBP computing in multiple architectures," Journal of Real Time Image Processing, 2014
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  • 19
    mlpy

    mlpy

    Machine Learning Python

    mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. mlpy provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, clustering and feature selection. mlpy is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3. mlpy is available both for Python >=2.6 and Python 3.X.
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  • 20
    The data complexity library, DCoL, is a machine learning software that implements all metrics to characterize the apparent complexity of classification problems. The code is implemented in C++ and can be run on multiple platforms.
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  • 21
    ALiVE
    A tool that helps develope the course of cognitive thought processes through software. This tool will look at the raw hex code of any input. It establishes pattern recognition over a mesured time incrament that in itself is at a different pace.
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  • 22
    Brainstormers Public Source Code Release
    The source code of the Brainstormers' RoboCup champion team 2005 has been made publicly available at the end of 2005. That source code release contains also a lot of our results in applying Reinforcement Learning in the simulated soccer domain.
    Downloads: 1 This Week
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  • 23
    This is C++ application code that implements Gene Expression Programming, or GEP - a form of genetic algorithm.
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  • 24
    Monk Computer Vision

    Monk Computer Vision

    A low code unified framework for computer vision and deep learning

    Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers. There are three libraries in this opensource set. - Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms. - Monk Object Detection -...
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  • 25
    GURLS

    GURLS

    Grand Unified Regularized Least Squares

    GURLS - (Grand Unified Regularized Least Squares) is a software package for training multiclass classifiers based on the Regularized Least Squares (RLS) loss function. The initial version has been designed and implemented in Matlab. Teh current goal is to implement an object-oriented C++ version to allow for a wider distribution of the library within the open-source developers' comunity. Main functionalities already implemented are: * Automatic parameter selection. * Handle massive datasets. * Great modularity, each method can be used independently. * Wide range of optimization routine. Please contact us if you want to join the developers' team or, otherwirse, feel free to download and use the library in your code and send us feedbacks about existing bugs, possible improvements and further developments.
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