Description: 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 Platform: |
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Author:杨 |
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Description: 利用CUDA实现了遥感数字影像处理基本算法中的拉普拉斯算子，并分别实现了采用Globalmemory、Sharedmemory，Texturememory进行数据传输，还同CPU中的串行代码进行了时间比较和误差分析。为了方便在服务器环境下测试运行，我们去掉了在Windows环境下对第三方库遥感影像库GDAL的依赖，而将遥感影像数据转成了二进制图像格式，对于输出影像也以同样的二进制格式存储。图像效果图通过专业遥感软件PCI或通用图像处理软件PhotoshopCS4打开。最后我们对计算结果进行了误差分析和加速比分析。-CUDA enables the use of remote sensing digital image processing the basic algorithm in the Laplace operator, and were achieved using Globalmemory, Sharedmemory, Texturememory data transmission, but also with the serial code CPU time comparison and error analysis. In order to facilitate the test run in the server environment, we have removed in the Windows environment for third-party remote-sensing image library GDAL library dependencies, but will switch to remote sensing image data into a binary image format, for the output images are also stored in the same binary format . Image Effect Picture through professional remote-sensing software, PCI or universal image processing software PhotoshopCS4 open. Finally, we calculated the results of the error analysis and speedup analysis. Platform: |
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Author:秦论剑 |
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Description: 利用CUDA实现了遥感数字影像处理基本算法植被指数，并分别实现了采用Globalmemory、Sharedmemory，Texturememory进行数据传输，还同CPU中的串行代码进行了时间比较和误差分析。为了方便在服务器环境下测试运行，我们去掉了在Windows环境下对第三方库遥感影像库GDAL的依赖，而将遥感影像数据转成了二进制图像格式，对于输出影像也以同样的二进制格式存储。图像效果图通过专业遥感软件PCI或通用图像处理软件PhotoshopCS4打开。最后我们对计算结果进行了误差分析和加速比分析。-CUDA enables the use of remote sensing digital image processing of basic algorithms vegetation index, and were realized using Globalmemory, Sharedmemory, Texturememory data transmission, but also with the serial code CPU time comparison and error analysis. In order to facilitate the test run in the server environment, we have removed in the Windows environment for third-party remote-sensing image library GDAL library dependencies, but will switch to remote sensing image data into a binary image format, for the output images are also stored in the same binary format . Image Effect Picture through professional remote-sensing software, PCI or universal image processing software PhotoshopCS4 open. Finally, we calculated the results of the error analysis and speedup analysis. Platform: |
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Author:秦论剑 |
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Description: cuda图像数据处理，压缩算法，自己也在学习不错的-cuda image data processing, compression algorithms, its also a good learning Platform: |
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Author:刘超 |
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Description: Convolution filtering is a technique that can be used for a wide array of image processing
tasks, some of which may include smoothing and edge detection. In this document we show
how a separable convolution filter can be implemented in NVIDIA CUDA and provide
some guidelines for performance optimizations. Platform: |
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Author:vgaliano |
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Description: 基于CUDA的高性能图像处理算法。着重介绍CPU和CUDA的计算能力，并详细介绍图像处理的背景以及几种操作的原理。在经过实验之后，对比CPU的计算能力可以发现，CUDA在并行处理数据的能力非常强大。由此可知，在图像处理的应用中，CUDA将大有可为。然而Hough变换的性能提升并不明显，其中的原子操作导致线程的排队，大幅度降低了线程并发性能，从而使得CUDA并行运算的优点不能显示出来，此问题的解决，有赖于对Hough变换并行算法的更深入研究。-CUDA-based high-performance image processing algorithms. Focuses on the computing power of CPU and CUDA, and detail the background of image processing and several operating principles. After experiments, comparing CPU' s computing power can be found, CUDA' s ability to process data in parallel is very strong. It can be seen in image processing applications, CUDA will be promising. Hough transform performance, however not obvious, which led to the thread queue atomic operations, significantly reduce the thread concurrency, which makes the advantages of CUDA parallel computing can not be displayed to solve this problem, parallel algorithm depends on the Hough transform more in-depth study. Platform: |
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Author:古月衣 |
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Description: 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。
-An Artificial Neural Network is an information processing method that was inspired by the way biological nervous systems function, such as the brain, to process information. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. Neural Networks have been widely used in "analogous" signal classifications, including handwriting, voice and image recognitions. Neural network can also be used in computer games. It enables games with the ability to adaptively learn from player behaviors. This technique has been used in racing games, such that opponent cars controlled by computers can learn how to drive by human players.
Since a Neural Network requires a considerable number of vector and matrix operations to get results, it is very suitable to be implemented in a parallel programming model and run on Graphics Processing Units (GPUs). Our goal is to utilize and unleash the power of GPUs to boost the performance o Platform: |
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Author:尘封 |
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Description: CUDA是Nvidia公司出的一个工具包，能对显卡进行编程，是学习图像处理进阶的好工具。-CUDA is Nvidia' s out of a kit that can be programmed on the card is a good learning tool for advanced image processing. Platform: |
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Author:路过 |
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Description: 一种基于CUDA的图像处理技术，可在c语言的基础上编译通过-CUDA-based image processing technology, based on the c language compiler Platform: |
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Author:蒋华 |
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Description: cuda5 and matlab code for Gaussian filtering and parallel image processing code, we hope to help Platform: |
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Author:ye |
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Description: python代码，基于CUDA图像处理的Python代码部分，希望对初学python的同学能有所帮助-python code, based on Python code section CUDA image processing, the hope of learning can help students python Platform: |
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Author:Moy |
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Description: Convolutional Neural Networks for No-Reference Image Quality Assessment(泛读)
Domain Transform for Edge-Aware Image and Video Processing
NVIDIA Update: CUDA Week in Review (Spotlight on Deep Neural Networks CUDA 6)
Skilling up for Oracle Fusion
Find person you are mostly like based on HMM image recogniti-Convolutional Neural Networks for No-Reference Image Quality Assessment(泛读)
Domain Transform for Edge-Aware Image and Video Processing
NVIDIA Update: CUDA Week in Review (Spotlight on Deep Neural Networks CUDA 6)
Skilling up for Oracle Fusion
Find person you are mostly like based on HMM image recogniti Platform: |
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Author:WEIMIN |
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Description: 图像处理 并行处理 matlab Since images can be represented by 2D or 3D matrices and the MATLAB processing engine
relies on matrix representation of all entities, MATLAB is particularly suitable for implemen‐
tation and testing of image processing workflows. The Image Processing Toolbox
™
(IPT)
includes all the necessary tools for general-purpose image processing incorporating more than
300 functions which have been optimised to offer good accuracy and high speed of processing.
Moreover, the built-in Parallel Computing Toolbox
™
(PCT) has recently been expanded and
now supports graphics processing unit (GPU) acceleration for some functions of the IPT.
However, for many image processing applications we still need to write our own code, either
in MATLAB or, in the case of GPU-accelerated applications requiring specific control over
GPU resources, in CUDA (Nvidia Corporation, Santa Clara, CA, USA).-the first part is dedicated to some essential tools of the IPT that can be used in
image analysis and assessment as well as in extraction of useful information for further
processing and assessment. These include retrieving information about digital images, image
adjustment and processing as well as feature extraction and video handling. The second part
is dedicated to GPU acceleration of image processing techniques either by using the built-in
PCT functions or through writing our own functions. Each section is accompanied by MAT‐
LAB example code. Platform: |
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Author:阿新 |
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Description: 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, using CUDA to write programs.) Platform: |
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Author:仁仁
|
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