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SIFT10M数据集,已用于评估近似近邻搜索方法

SIFT10M数据集,已用于评估近似近邻搜索方法

7.3G
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Computer Causal-Discovery

Xiping Fu, Brendan McCane, Steven Mills, Michael Albert and Lech SzymanskiDepartment of Computer Science, University of......

数据结构 ? 7.3G

    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    Xiping Fu, Brendan McCane, Steven Mills, Michael Albert and Lech Szymanski
    Department of Computer Science, University of Otago, Dunedin, New Zealand
    {xiping, mccane, steven, malbert, lechszym}@cs.otago.ac.nz


    Data Set Information:

    In SIFT10M, the titles of the png files indicate the columns position of the SIFT features. This data set has been used for evaluating the approximate nearest neighbour search methods. The patches can be used for visualisation purpose and helps for analysing the performance of the corresponding approximate nearest neighbour search methods.


    Attribute Information:

    Each SIFT feature is a 128D column, and the corresponding patch is saved in  41*41 png format. The png files are compressed into 307 tar files for downloading.


    Relevant Papers:

    Xiping Fu, Brendan McCane, Steven Mills, and Michael Albert, 'NOKMeans: Non-orthogonal K-means hashing', in Asian Conference on Computer Vision (ACCV14). pp 162--177.
    Xiping Fu, Brendan McCane, Steven Mills, Michael Albert, and Lech Szymanski, 'Auto-JacoBin: Auto-encoder Jacobian Binary Hashing', submitted to PAMI.



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