Search Results for "data visualization, research"

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...

///////// NOTICE We have migrated to GitHub: https://petavision.github.io To clone an updated repository of the PetaVision codebase, please go to our page on GitHub. ///////// PetaVision is an open source, object oriented neural simulation toolbox optimized for high-performance multi-core, multi-node computer architectures. PetaVision is intended for computational neuroscientists who seek to apply neuromorphic models to hard signal processing problems; both to improve on the...

...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 fluorescence microscopes, (2) scalability, by analyzing advanced stages of development with up to 20,000 cells per time point, at 26,000 cells min-1 on a single computer workstation, and (3) ease of use, by adjusting only two parameters across all data sets and providing visualization and editing tools for efficient data curation. ...

BNNS is a research tool for interactive training of artificial neural networks based on the Response Function Plots visualization method. It enables users to simulate, visualize and interact in the learning process of a Multi-Layer Perceptron on tasks which have a 2D character. Tasks like the famous two-spirals task or classification of satellite image data.

Customizable software to smoothly fit non-linear, high-dimensional data. SDK in C with C++ wrappers, plus demo applications (all under LGPL). Versions under Windows and Linux already operational. Further progress depends on your imagination!

A High-Order Multi-Variate Approximation Scheme for Arbitrary Data Sets, C implementation of the method described in http://web.mit.edu/qiqi/www/paper/interpolation.pdf, with Python and Fortran interfaces.

With miao3d you can train a specific Gaussian Markov Random Field (GMRF) that then can be used to estimate a depthmap ("3D"), given an image ("2D"). A GUI allows inspection of the image + depthmap.