搜索资源列表
2D CUDA-based bilinear interpolation
- This MEX performs 2d bilinear interpolation using an NVIDIA graphics chipset. To compile and run this software, one needs the NVIDIA CUDA Toolkit (http://www.nvidia.com/object/cuda_get.html) and, of course, an NVIDIA graphics card of reasonably moder
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_histogram
- 在matlab中可以调用的程序，用c语言编写，cuda求直方图-used in caculating histogram of color images ,
hpec07_cuda_final
- pdf file see Accelerating MATLAB with CUDA The MATLAB scr ipts solve the Euler equation in vorticitystream function using a pseudo-spectral method
SOMbach
- Self organizing maps for Matlab CUDA
jacket_matlab
- 在matlab下编程使用jacket工具包进行GPU加速图像平滑算法，对900×900的图像平滑可达8倍多的加速比。需要jacket工具包及cuda toolkit。-In matlab programming toolkit used jacket GPU-accelerated image smoothing algorithm, the 900,900 image smooth acceleration up to 8 times more than that. Need jacket t
DLTcode
- Robust Non-negative Dictionary Learning for Visual Tracking The provided codes could be either embedded into the benchmark framework of paper Online Object Tracking: A Benchmark (CVPR2013) (You can find details here: http://visual-tracking.net/) or
CorrectionImage
- 这是在Matlab软件平台下的 GPU程序，进行图像放大的并行运算，使用CUDA来编写程序。(This is in the Matlab software platform under the GPU program, image amplification parallel operation, using CUDA to write programs.)
GPUBarCode
- 这是在Matlab软件平台下的 GPU程序，用最近邻域双线性插值算法填补图像中缺失区域，是并行运算处理，使用CUDA来编写程序。(This is the GPU program under the Matlab software platform, and the nearest neighborhood bilinear interpolation algorithm to fill the missing areas in the image is parallel processing,
loadcaffe-master
- 通过caffe和matlab，实现cnn网络(supported by https://github.com/soumith/inception.torch NN support means both CPU and GPU backends. You can also use Caffe inside Torch with this: https://github.com/szagoruyko/torch-caffe-binding However you can't use bo
marchingCubes
- 1.在MATLAB中直接实现Marching Cubes; 2.使用了向量化和预分配的概念在MATLAB中优化; 3.用c-mex函数和GPU实现.(1. Marching Cubes is realized directly in MATLAB; 2., the concepts of VQ and pre allocation are optimized in MATLAB. 3. is implemented with c-MEX function and GPU.)