Search Results for "artificial intelligence linux"

Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. 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...

Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is...

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...

XTCC/Qscript revolves around two concepts: 1) Data collection : Qscript 2) Data analysis : XTCC Qscript enables Market Research companies to securely collect data using online and offline mediums such as web, tablets/mobile. Different products include: 1) Pen and Paper Survey Management Qscript enables faster and easier keyboard entry with real time logic and validation. It generates SPSS and IBM Quantum compatible data tabulation programs leading to significant time savings of up...

BIL++ is a set of standalone C++ packages for data processing in Bioinformatics (Graph mining, Bayesian networks, Genetic algorithm, Discretization, Gene expression data analysis, Hypothesis testing).

This library implements self-organizing neural networks, also called Kohonen Nets. They can be used for high dimensional data analysis. Example: content based image recognition ( CBIR ).