搜索资源列表
CUDA_BP_neuralnetwork
- 基于nvidia CUDA架构的BP神经网络程序，在G80,G92 GPU上可以完成BP神经网络训练。速度较双核CPU提高十倍
CUDA.rar
- 文章介绍如何使用CUDA实现神经网络，并把他应用在GPU图像处理单元上,The article describes how to use CUDA to achieve neural networks, and he applied to image processing unit on the GPU
VisionWorkbench_1.1.0.5_x86
- 在计算机图像硬件上实现计算机视觉的相关算法，并使用了OpenGL及其Cg语言和CUDA，程序不错。-The OpenVIDIA project implements computer vision algorithms on computer graphics hardware, in OpenGL and Cg and CUDA. The project provides useful example programs which run computer vision algorithms
cuSVMVCcode
- 基于GPU计算的SVM，VC++源码，包括详细文档说明文件。借用了GPU编程的优势，该代码据作者说比常规的libsvm等算法包的训练速度快13-73倍，预测速度快22-172倍。希望对大家有用-cuSVM is a software package for high-speed (Gaussian-kernelized) Support Vector Machine training and prediction that exploits the massively parallel proc
cuda-GPU
- 本文详细分析了Tesla GPU图形与计算架构和CUDA统一计算设备架构，详细描述了如何对计算任务进行并行分解，并通过CUDA的双层并行编程模型映射到Tesla GPU上。 在本文的实现部分，以软件开发流程为主线，描述了如何利用CUDA实现模式识别中的三种常用算法-The paper analyzed the Tesla GPU computing architecture and CUDA graphics and computing devices unified architecture,
GPUNN_GUI
- 改代码是基于CUDA GPU的神经网络的实施。-This article describes the implementation of a neural network with CUDA..
gpupgasav2
- 基于GPU并行的模拟退火算法，使用CUDA,结合遗传算法，自适应邻域的并行模拟题退火算法-Simulated annealing algorithm based on GPU parallel With CUDA, combined with genetic algorithm, the adaptive neighborhood annealing algorithm for parallel simulation questions
Convolution_GPU
- This project implement the convolution neural network on GPU. This reduce much time for training process. This project was written in C# and cuda
cuda-convnet
- 卷积神经网的GPU高效并行实现，用于大规模图像识别-A efficient GPU implementation of CNN with application to large-scale image recognition
cuda_monte_carlo
- 这是论文 On the Utility of Graphics Cards to Perform Massively Parallel Simulation of Advanced Monte Carlo Methods 的配套代码,对于了解GPU cuda并行编程有用.-This is the thesis " On the Utility of Graphics Cards to Perform Massively Parallel Simulation of Advanced Mo
darknet-master
- 是一种神经网络框架，在其基础上可以实现物体检测，图像分类，模式识别功能。(Darknet is a neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation. You can find the source on GitHub or you can read more about what Darknet can do righ
win10配置tensorflow gpu版不用装CUDA
- 这是本人写的一篇安装tensorflow的方法，用于win10系统，gpu版(This is an article written by myself for installing tensorflow gpu version.)