cudnn-linux-x86_64-8.9.6.50_cuda11-archive.tar.xz 适合操作系统为:linux , 需要配合 cuda12.
2024-04-09 16:11:15 824.88MB linux cudnn cuda
1
cuda 12.1 nvrtc-builtins64_121.dll
2024-03-19 14:01:05 6.68MB cuda
1
keras安装步骤的ppt 1、ANACONDA 安装 2、Cuda及cuDNN安装 3、Tensorflow-gpu版本安装 4、Keras安装 5、Anaconda的使用 6、Keras分类示例
2024-03-09 14:14:36 4.3MB tensorflow tensorflow anaconda keras
1
里面有对应cuda9.0 、cuda9.2、 cuda10.2三个版本的cuDNN。 版本为windows10 64位 小伙伴按需下载!!
2024-02-29 15:22:54 426.15MB cuda cuDNN win10x64 tensorflow
1
MPI和CUDA在多层快速多极子中的应用,李朕,陆卫兵,多层快速多极子(MLFMA)技术是计算电磁学的分支。采用多种并行技术对多层快速多极子技术进行并行加速,是提高其计算能力行之有效�
2024-01-14 09:52:22 433KB 首发论文
1
杰森SIFT 这是一个 CUDA 加速的 SIFT 关键点提取实现。 请注意,它目前仅在第一个八度音阶上执行提取。 输入以下命令进行编译: cd jetsonSIFT mkdir build cd build cmake ../src 该程序的使用如下: ./jetsonSIFT yourimage.jpg 样本: ./jetsonSIFT ../images/lenna.jpg 如果您收到有关不受支持的 CUDA 架构规范的错误,请编辑arch=compute\_32,code=sm\_32行以匹配您的 (Nvidia) 卡支持的最新架构。
2023-12-15 10:17:27 118KB Cuda
1
SIFT-GPU A CUDA implementation of SIFT: 配置 (待完成)见SIFT-GPU配置教程 测试 1.Release 模式 cd bin ./SimpleSIFT.exe Release模式,输出结果: [GPU VENDOR]: NVIDIA Corporation 1717MB TEXTURE: 16384 Image size : 800x600 Image loaded : ../data/800-1.jpg Features: 3358 Features MO: 3923 Image size : 640x480 Image loaded : ../data/640-1.jpg Features: 2383 Features MO: 2791 2279 sift matches were
2023-12-15 09:39:08 43.14MB gpu cuda sift
1
Samples for CUDA Developers which demonstrates features in CUDA Toolkit. This version supports [CUDA Toolkit 12.2] NVIDIA 官方 Samples样例,支持CUDA12.2
2023-11-04 16:41:24 139.74MB cuda
1
精通GPU-利用CUDA加速图像处理,提升缺陷检测精度,CSDN CSDN组织关于GPU 方面的视频
2023-10-09 13:58:25 930.6MB 图像处理
1
This book is roughly divided into four sections. Chapter 1 presents a technique for embedding class labels into a feature set in such a way that generative exemplars of the classes can be found. Chapters 2 and 3 present signal and image preprocessing techniques that provide effective inputs for deep belief nets. Special attention is given to preprocessing that produces complex-domain features. Chapter 4 discusses basic autoencoders, with emphasis on autoencoding entirely in the complex domain. This is particularly useful in many fields of signal and image processing. Chapter 5 is a reference for the DEEP program, available as a free download from my web site.
2023-09-26 15:03:49 5.51MB c++ cuda 语言
1