Search Results for "nero linux 4"
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Showing 10 open source projects for "nero linux 4"
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Technical analysis library with indicators like ADX, MACD, RSI, Stochastic, TRIX... includes also candlestick pattern recognition. Useful for trading application developpers using either Excel, .NET, Mono, Java, Perl or C/C++.
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SkyTracer is a desktop software intended for data collection in radioastronomical observations, as well as data collection for other uses. It's interface aims to be rich and easy to use. Data collection can be achieved by one of these devices: PICADC (free Microchip PIC solution developed by me [will make publicly available soon]), MC Measurement Computing (MCC) board or any Sound Card with Line In or Mic input (used for spectral analysis).
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A Crossplatform OpenGl Gui for a Accelerometer (via USART/Atmega).
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ANOSE is a web application (a web site) that allows software engineers to collect information about software projects and perform statistical analysis on the data collected. A key goal in ANOSE is to provide an easy to use user interface and efficient da
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Cloudster is a generic and parallel implementation of the k-means algorithm. It is written in C# and uses the Windows Azure environment.
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CVSharp (aka Computer Vision in C#) is a Computer Vision project. Until the present day just one part of the whole project was actually developed. It's called CVSharp Lab, an Image Processing Tool.
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n-squared is a light weight, super powered note pad application that stores notes in an embedded database for easy searching. It has a tabbed interface, syntax highlighting, encryption, and more!
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ISIADIS: development environment for hierarchical software systems. ISIADIS allows prototyping, development and running software systems that are based on hierarchical (tree-like) architecture.
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The NSketch library provides implementations of most common sketch-based algorithms (histograms, quantile, frequent items, bloom filter ...). The library is written in C# for .Net.
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NSvm is a .Net Support Vector Machine library written in .Net. NSvm features the SMO algorithm, a few kernels (including ad hoc algorithms for linear kernels). The objectives of NSvm are simplicity, flexibility and extensibility.
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