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基于内容的多媒体数据库检索算法: 用于最近邻搜索的R*-tree算法-content-based multimedia database search algorithm : Nearest Neighbor Search for the R *- tree algorithm
Update : 2008-10-13 Size : 959.87kb Publisher : 章明

用VC。NET2005实现优秀的最近邻搜索算法LB-TREE的模拟和图形显示。具有建立优良数据结构和搜索功能-VC.NET2005 achieve outstanding nearest neighbor search algorithm LB-TREE simulation and graphics. With excellent data structure and search functions
Update : 2008-10-13 Size : 3.53mb Publisher : yangtao

The approximate nearest neighbor search code is contained in this zip file. You can use the data contained in to see how the program works.
Update : 2008-10-13 Size : 611.3kb Publisher : jianzhuhuai

DL : 0
基于内容的多媒体数据库检索算法: 用于最近邻搜索的R*-tree算法-content-based multimedia database search algorithm : Nearest Neighbor Search for the R*- tree algorithm
Update : 2025-02-17 Size : 960kb Publisher : 章明

假近邻法(False Nearest Neighbor, FNN)计算嵌入维的Matlab程序 文件夹说明: Main_FNN.m - 程序主函数,直接运行此文件即可 LorenzData.dll - 产生Lorenz时间序列 PhaSpaRecon.m - 相空间重构 fnn_luzhenbo.dll - 假近邻计算主函数 SearchNN.dll - 近邻点搜索 buffer_SearchNN_1.dll - 近邻点搜索缓存1 buffer_SearchNN_2.dll - 近邻点搜索缓存2 参考文献: M.B.Kennel, R.Brown, H.D.I.Abarbanel. Determining embedding dimension for phase-space reconstruction using a geometrical construction[J]. Phys. Rev. A 1992,45:3403. -false neighbors (False Nearest Neighbor, FNN) calculation embedding dimension of the Matlab program folder : Main_FNN.m-procedure main function, Direct operating this document can be LorenzData.dll-time series produced Lorenz PhaS paRecon.m-phase space reconstruction fnn_luzhenbo.dll-calculated at the main function neighbors SearchNN.dll-point search buffer_SearchNN_1.dll neighbor- Search neighbor point a buffer_SearchNN_2.dll Cache-Cache Search neighbors point two reference Literature : M. B. Kennel, R. Brown, H. D. I. Abarbanel. Determining embedding dime nsion for phase-space reconstruction using a g eometrical construction [J]. Phys. Rev. A 1992 , 45:3403.
Update : 2025-02-17 Size : 97kb Publisher : 呆雁

DL : 0
用VC。NET2005实现优秀的最近邻搜索算法LB-TREE的模拟和图形显示。具有建立优良数据结构和搜索功能-VC.NET2005 achieve outstanding nearest neighbor search algorithm LB-TREE simulation and graphics. With excellent data structure and search functions
Update : 2025-02-17 Size : 3.96mb Publisher : yangtao

经典的ann算法,最近邻域搜索,是图像处理,图形图像编程中有用的工具。-Ann classic algorithms, nearest neighbor search domain is image processing, graphics, images programming useful tool.
Update : 2025-02-17 Size : 217kb Publisher : 刘飞

DL : 0
ANN是一个加快搜索速度的源码程序;通过C++编写,支持在任意高维空间的近似或准确的最近邻搜索。-ANN is a source to speed up the search speed of procedures through C++ Prepared to support the arbitrary high-dimensional space approximate or accurate nearest neighbor search.
Update : 2025-02-17 Size : 54kb Publisher :

% [nearest_neighbours] = find_nearest_neighbours( database, desc, max_dist ) % Find the indices of the nearest neighbours of the given desriptors in the近邻点寻找算法,在非线性时间序列中很有用,是常用的算法- [Nearest_neighbours] = find_nearest_neighbours (database, desc, max_dist) Find the indices of the nearest neighbours of the given desriptors in the neighbor-point search algorithm, the nonlinear time series of very useful, is a commonly used algorithm
Update : 2025-02-17 Size : 1kb Publisher : zhxj

The approximate nearest neighbor search code is contained in this zip file. You can use the data contained in to see how the program works.
Update : 2025-02-17 Size : 611kb Publisher : jianzhuhuai

k NN algorithm nearest neighbor search
Update : 2025-02-17 Size : 1kb Publisher : Namrata

一个高效的k-d tree实现,可以广泛的应用与图形图像处理。-K nearest neighbor search based on KD-tree
Update : 2025-02-17 Size : 24kb Publisher : 南亮亮

最近邻搜索算法,k_tree算法的大部分中文文献-Nearest neighbor search algorithm, k_tree algorithm for most of the Chinese literature
Update : 2025-02-17 Size : 11.21mb Publisher : zoe

DL : 0
code for approximate nearest neighbor search
Update : 2025-02-17 Size : 603kb Publisher : rui

大规模图像检索的代码,matlab与c++混合编程。总结了目前图像检索领域目前主要存在的方法。通过阅读该代码,可以对于经典的“词袋”模型(bow模型)有个具体的了解,但是该代码没有提供前序的特征提取,是直接从对提取好的特征向量聚类开始的,包括了k-means,分层k-means(HKM)聚类,倒排文件的建立和索引等,该代码还提供了局部敏感哈希(LSH)方法。最后,这份代码是下面这篇论文的作者提供的, Indexing in Large Scale Image Collections: Scaling Properties and Benchmark-This C++/Matlab package implements several algorithms used for large scale image search. The algorithms are implemented in C++, with an eye on large scale databases. It can handle millions of images and hundreds of millions of local features. It has MEX interfaces for Matlab, but can also be used (with possible future modifications) from Python and directly from C++. It can also be used for approximate nearest neighbor search, especially using the Kd-Trees or LSH implementations. The algorithms can be divided into two broad categories, depending on the approach taken for image search: 1. Bag of Words: ---------------- The images are represented by histograms of visual words. It includes algorithms for computing dictionaries: * K-Means. * Approximate K-Means (AKM). * Hierarchical K-Means (HKM). It also includes algorithms for fast search: * Inverted File Index. * Inverted File Index with Extra Information (for example for implementing Hamming Embedding). *
Update : 2025-02-17 Size : 145kb Publisher : 薛振华

一种用近邻搜索法解决VRP问题的源代码,可以解决多种问题-Source code of a nearest neighbor search method to solve the VRP problem
Update : 2025-02-17 Size : 5kb Publisher : 孙常虹

对大量文件中相关内容的搜索,k近邻查询算法及一些改进-A large number of files in the search k nearest neighbor query algorithm and some improvements
Update : 2025-02-17 Size : 4.46mb Publisher : wyj

Batch Nearest Neighbor Search for Video Retrieval
Update : 2025-02-17 Size : 697kb Publisher : Silkilya

自适应空间球的k邻域快速搜索算法,利用空间微分块与动态球策略的k近邻搜索算法研究-Origianl-Adaptive spatial neighborhood k ball fast search algorithm, differential block the use of space and dynamic ball strategy k nearest neighbor search algorithm-Origianl
Update : 2025-02-17 Size : 373kb Publisher : 闫子熙

Conventional spatial queries, such as range search and nearest neighbor retri , involve only conditions on objects’ geometric properties. Today, many modern applications call for novel forms of queries that aim to find objects satisfying both a spatial predicate, and a predicate on their associated texts. For example, instead of considering all the restaurants, a nearest neighbor query would instead ask for the restaurant that is the closest among those whose menus contain “steak, spaghetti, brandy” all at the same time.-Conventional spatial queries, such as range search and nearest neighbor retri , involve only conditions on objects’ geometric properties. Today, many modern applications call for novel forms of queries that aim to find objects satisfying both a spatial predicate, and a predicate on their associated texts. For example, instead of considering all the restaurants, a nearest neighbor query would instead ask for the restaurant that is the closest among those whose menus contain “steak, spaghetti, brandy” all at the same time.
Update : 2025-02-17 Size : 3mb Publisher : pravin
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