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Bayesian Classification with Gaussian Processes.pdf文章的实现代码
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SiftGPU 是SIFT特征为GPU执行。 SiftGPU进程像素平行建立高斯金字塔的技术要点。基于GPU的清单生成，SiftGPU然后使用的GPU / CPU的混合方法，有效地建立紧密特征点的名单。并行处理技术要点最后得到他们的方向和描述。-SiftGPU is an implementation of SIFT for GPU. SiftGPU processes pixels parallely to build Gaussian pyramids and detect DoG Key
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使用gpu、cpu并行进行sift算子计算匹配，能够在原来的基础上加速处理，但对显卡要求较高，具体环境配置使用方法可以参照mannual-SiftGPU is an implementation of SIFT [1] for GPU. SiftGPU processes pixels parallely to build Gaussian pyramids and detect DoG Keypoints. Based on GPU list generation[3], SiftGPU th
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高斯过程工具箱。由C++编制而成。适用于大规模非均质数据的回归及插值运算。-Gaussian Process Toolkit (GPTK) is a C++ library providing regression/interpolation methods based on Gaussian Processes.
In particular the toolkit implements a projected sequential Gaussian process method (p
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NETLAB algorithms for PR+书籍代码。学习模式识别的很好的老外书籍。基础模型很多，代码很细致，有很多算法的实现细节，对于应用很有帮助，-chapter covers a group of related pattern recognition techniques and includes a range of examples to show how these techniques can be applied to solve practical problems.
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It is a series of tests to show how to sample Gaussian processes in Python and multivariate functions in order to get random functions-It is a series of tests to show how to sample Gaussian processes in Python and multivariate functions in order to
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