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University of Sopron
- Hungary, Sopron
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Simplified MEPDG-Based M-E design tool for flexible pavements. Specially crafted for Uruguayan input data sources.
Flexibility evaluation in the design of flexible pavement
High-performance C++/Python library for 5-layer elastic half-space deflection. Features analytical gradients, ms-level back-calculation, and uncertainty analysis.
primuszp / ALVA
Forked from asmusskar/ALVAALVA is a MATLAB-package for advanced pavement modeling that is highly adaptive
Python tool for converting files and office documents to Markdown.
The official implementation of CircleNet, MICCAI 2020
Use of MC Dropout for Finite Element Response Prediction of Flexible Pavements
Quick tutorial of scientific computing with Python using a real physics application.
Pytorch based network to recognize and classify 2d circles
A computer program that predicts the time available to compact an asphalt pavement
LynFarm computes responses in an asphalt pavement under the loads of farming vehicles that utilize ribs. LynFarm is an add-on package to ALVA by Asmus Skar.
3D Layered Elastic Analysis running on Python
Pytorch framework for doing deep learning on point clouds.
Official PyTorch implementation of Superpoint Transformer [ICCV'23], SuperCluster [3DV'24 Oral], and EZ-SP [ICRA'26]
Python and Matlab codes to paper: F. Sroubek, M. Sorel, J. Zak: Precise International Roughness Index Calculation. Int. J. Pavement Res. Technol. (2021). https://doi.org/10.1007/s42947-021-00097-z
Simple and lightweight computational geometry library for .Net
ZacCAD is developed on the basis of SharpCAD. It is a very simple 2D CAD drawing application developed by C#.
A simple and user-friendly framework for writing small graphical apps in C#.
A python script for the design of new flexible pavements to CD226
Structural analysis of pavement with consideration of inelastic material properties of structural layers. Formulation and numerical implementation of non-classical constitutive models of asphalt-ag…
PyTorch implementation of "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" https://arxiv.org/abs/1612.00593
LiDAR point cloud ground filtering / segmentation (bare earth extraction) method based on cloth simulation
Fast Delaunay triangulation of 2D points implemented in C#.