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Vincent Shao's Projects

aabbtree icon aabbtree

Ported from Javascript (https://github.com/turbulenz/turbulenz_engine)

antlr4 icon antlr4

ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files.

antlr4cs icon antlr4cs

The original, highly-optimized C# Target for ANTLR 4

awesome-cpp icon awesome-cpp

A curated list of awesome C/C++ frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.

awesome-dotnet-core icon awesome-dotnet-core

:honeybee: A collection of awesome .NET core libraries, tools, frameworks and software

bgfx icon bgfx

Cross-platform, graphics API agnostic, "Bring Your Own Engine/Framework" style rendering library.

bimsurfer icon bimsurfer

The first open source WebGL based IFC viewer

boost icon boost

Super-project for modularized Boost

box2d icon box2d

Automatically exported from code.google.com/p/box2d

captura icon captura

Capture Screen, Audio, Cursor, Mouse Clicks and Keystrokes

carve icon carve

Automatically exported from code.google.com/p/carve

carve-1 icon carve-1

Carve is a fast, robust constructive solid geometry library. (fork from https://code.google.com/p/carve/)

carvesharp icon carvesharp

.NET Wrapper for Carve's CSG and mesh boolean operations

cesium icon cesium

An open-source JavaScript library for world-class 3D globes and maps :earth_americas:

cgal icon cgal

The public CGAL repository, see the README below

cork icon cork

3D Boolean / CSG Library

csg icon csg

Solid modeling library for .NET

csg.js icon csg.js

Constructive solid geometry on meshes using BSP trees in JavaScript

dapper icon dapper

Dapper - a simple object mapper for .Net

dapper.simplecrud icon dapper.simplecrud

Who wants to write basic read/insert/update/delete statements? SimpleCRUD provides simple CRUD helpers for Dapper.

de4dot icon de4dot

.NET deobfuscator and unpacker.

deeplearntoolbox icon deeplearntoolbox

Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.

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