Showing 8 open source projects for "small linux"

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    dlib

    dlib

    Toolkit for making machine learning and data analysis applications

    ...Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is about 1 to 4. The library is tested regularly on MS Windows, Linux, and Mac OS X systems. No other packages are required to use the library, only APIs that are provided by an out of the box OS are needed. There is no installation or configure step needed before you can use the library. All operating system specific code is isolated inside the OS abstraction layers which are kept as small as possible.
    Downloads: 4 This Week
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  • 2
    CT4AM

    CT4AM

    Tools for 3D image analysis of additively manufactured parts

    CT4AM is a cross-platform toolkit for 3D-image processing in the domain of additive manufacturing for toolpath visualisation or correlation to tomographic data and related materials science. It is written in C++ and provides small, problem-specific applications for viewing, analysing and visualising of volumetric data from micro-CT scans with respect to the complex process parameters and characteristics of additive manufacturing. Moreover, data analysis and processing of G-code are key...
    Downloads: 0 This Week
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  • 3
    mzMatch is a Java collection of small commandline tools specific for metabolomics MS data analysis. The tools are built on top of the PeakML core library, providing mass spectrometry specific functionality and access to the PeakML file format.
    Downloads: 2 This Week
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  • 4
    DocWire SDK

    DocWire SDK

    Award-winning modern data processing SDK in C++20

    DocWire SDK, a standout C++20AI driven data processing tool, has received award from SourceForge and strong backing from Microsoft. It handles nearly 100 file types, empowering efficient text extraction, web data extraction, and document analysis. For businesses, the shift to DocWire SDK signifies a leap forward. It promises comprehensive document format support and the ability to extract valuable insights from email boxes, databases, and websites using cutting-edge AI. DocWire SDK aims to...
    Downloads: 1 This Week
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  • 5

    PINCIS

    PINCIS.pl is a Perl bioinf. script to analyze PICS data

    PINCIS.pl (PIcs N-/C-terminal Inferred Substrates perl script) is a small, command line tool to designate and analyze PICS (Schilling et al., Nat. Protocols, 2011) data to gain the prime and non-prime site specificity of proteases. Thus, the script filters given peptide lists for library peptides (generated by the digestion protease in the proteomics workflow rather then the protease of interest) and prints out lists of inferred N- and C-terminal cleavage window extensions which can be...
    Downloads: 0 This Week
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  • 6
    The application helps you with your statistics assignment help. Our Stata assignment help is popular among students following course economics and political science. We offer R assignment help for data analysis as well as graphical user interface although SPSS looks a lot like excel but mostly students avail our excel assignment help for small datasets and SPSS assignment help for larger datasets. For assistance you can email us at info@statisticshomeworkhelper.com .
    Downloads: 1 This Week
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  • 7
    Zika-RNAseq-Pipeline

    Zika-RNAseq-Pipeline

    An open RNA-Seq data analysis pipeline tutorial

    RNA-seq analysis is becoming a standard method for global gene expression profiling. However, open and standard pipelines to perform RNA-seq analysis by non-experts remain challenging due to the large size of the raw data files and the hardware requirements for running the alignment step. Here we introduce a reproducible open source RNA-seq pipeline delivered as an IPython notebook and a Docker image. The pipeline uses state-of-the-art tools and can run on various platforms with minimal...
    Downloads: 0 This Week
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  • 8
    JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks...
    Downloads: 0 This Week
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