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This implementation is able to create pruned and unpruned C4.5 decision trees.
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In this context, the proposed implementation is able to work in real time with high-resolution spatial grids and using up to 48 microphones.
Our method is implemented in parallel and the current implementation is able to handle systems with at least thousands of atoms.
The implementation is able to perform up to 4.1⋅109 Monte Carlo moves per second.
The GPGPU implementation is able to provide up to 29 FPS for 35 iterations of the super-resolution algorithm.
A MATLAB implementation is able to classify more than 5000 spikes per second on a modern workstation.
The implementation is able to handle general curvilinear coordinates, for which restriction and prolongation formulae are presented along with boundary treatments at 'singular' boundaries.
Results show that the present implementation is able to exhibit good stability and accuracy properties for high Reynolds number flows with unstructured meshes.
The results also showed that a tailored implementation is able to perform faster than a more general one by orders of magnitude, while providing similar quality.
Regarding coding speed, the results show that our proposed implementation is able to compress a full-HD (1080p) resolution picture at 1,581 fps.
Disparity map quality evaluations on Middlebury benchmark and real-world outdoor scenery show that the proposed implementation is able to generate high quality disparity maps.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com