Search Results for "wavelet transform c"
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Showing 9 open source projects for "wavelet transform c"
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.NET Multi-platform App UI
.NET MAUI is the .NET Multi-platform App UI
.NET Multi-platform App UI (.NET MAUI) is a cross-platform framework for creating mobile and desktop apps with C# and XAML. Using .NET MAUI, you can develop apps that can run on Android, iOS, iPadOS, macOS, and Windows from a single shared codebase. .NET Multi-platform App UI (.NET MAUI) is the evolution of Xamarin.Forms that expands capabilities beyond mobile Android and iOS into desktop apps for Windows and macOS. With .NET MAUI, you can build apps that perform great for any device that runs... -
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FileHelpers
The FileHelpers are a free and easy to use .NET library to read/write
FileHelpers is a free and easy-to-use .NET library to import or export data from fixed length or delimited records in files, strings or streams. You can strongly type your flat file (fixed or delimited) by simply describing a class that maps to each record and later read or write your file as a strongly typed .NET array. The library also has support to import or export data from different data storage types like Excel, Access, SqlServer, etc. In almost every project there is a need to read... -
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.NET for Apache Spark
A free, open-source, and cross-platform big data analytics framework
.NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write .NET... -
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JPPF
The open source grid computing solution
JPPF makes it easy to parallelize computationally intensive tasks and execute them on a Grid. -
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5
Accord.NET Framework
Machine learning, computer vision, statistics and computing for .NET
The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start to get up and running quickly, and extensive documentation and a wiki help fill in the details. The Accord.NET project provides... -
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MMMarkdown
An Objective-C framework for converting Markdown to HTML
MMMarkdown is an Objective-C framework for converting Markdown to HTML. It is compatible with OS X 10.7+, iOS 8.0+, tvOS, and watchOS. Unlike other Markdown libraries, MMMarkdown implements an actual parser. It is not a port of the original Perl implementation and does not use regular expressions to transform the input into HTML. MMMarkdown tries to be efficient and minimize memory usage. -
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XMLNuke
A Web Development Framework focused on the Data
== THIS PROJECT HAS MOVED TO https://github.com/byjg/xmlnuke == XMLNuke is a Web Development Framework focused on produce the data. You can to create applications very rich by producing natively XML or JSON and the Framework transforms this data to another formats including XHTML. -
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Trx Framework
.NET project for financial messages interchange supporting ISO 8583
Trx Framework allows to build client/server applications to interchange financial messages. It supports many encoding/decoding mechanisms for fixed and variable field messages, including ISO 8583, XML and conditional formatting. It is highly customizable and extensible. Trx Framework also provides a flexible channel communication infrastructure supporting TCP/IP and other technologies. -
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A Functor / "Function Object" library, providing classes implementing an operator(). A substantial improvement (IMHO) over what the standard provides, with composition, arithmetic expressions, "transform" operations, the naming convention and more.
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