The proliferation of information housed in computerized domains makes it vital to find tools to search these resources efficiently and effectively. Ordinary retrieval techniques are inadequate because sorting is simply impossible. Consequently, proximity searching has become a fundamental computation task in a variety of application areas. Similarity Search focuses on the state of the art in developing index structures for searching the metric space. Part I of the text describes major theoretical principles, and provides an extensive survey of specific techniques for a large range of applications. Part II concentrates on approaches particularly designed for searching in large collections of data. After describing the most popular centralized disk-based metric indexes, approximation techniques are presented as a way to significantly speed up search time at the cost of some imprecision in query results. Finally, the scalable and distributed metric structures are discussed.
2021-08-10 16:00:00 11.61MB Similarity Search Metric Space
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Foundations of Multidimensional and Metric Data Structures
2021-08-08 11:01:24 56.42MB Data Structures
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HOTA - A Higher Order Metric for Evaluating Multi-object Tracking
2021-07-24 18:03:34 3.59MB HOTA Tracking
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Metric Studio用户指南,方便入门新手使用
2021-07-23 18:57:19 965KB Metric Studio
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Cognos® 8 Business Intelligence(METRIC STUDIO 用户指南)
2021-07-10 17:33:51 1.34MB METRIC STUDIO 用户指南
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信息年龄(AoI)是在2010年代初引入的,目的是表征系统对远程观察到的过程的知识的新鲜度。 事实证明,AoI是从根本上来说是一种新颖的时间度量标准,与现有的延迟和等待时间显着不同。 这种工具的重要性是至关重要的,尤其是在信息传输以外的情况下,因为通信也是为了控制,计算,推断而不仅仅是复制源消息而发生的。 本书介绍了当前的内容,并讨论了有关AoI的第一批作品,并讨论了可能产生更具挑战性和趣味性的研究的未来方向。
2021-07-06 16:43:14 4.41MB 信息年龄 AoI
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kube1.17,dashboard,metres-server部署文档整理,centos7.x以上已经完成部署,亲测好用。
2021-06-10 14:20:03 106KB k8s kubernetes dashboard metric-server
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flink自定义metric中只显示metric不显示metricgroup
2021-04-18 09:06:44 13KB flink prometheus metric
这个资源复现的是MatchNet:Unifying Feature and Metric Learning for Patch-Based Matching。对于图像匹配在深度学习方面的应用。使用的是keras框架。具体实现可以看这篇博客https://blog.csdn.net/weixin_42521239/article/details/103989934
2021-03-11 15:46:36 17.25MB keras matchnet 图像匹配 深度学习
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This paper takes the p-adic representation of integers as the research object to realize the distance measurement of integers in the p-adic metric space. The authors firstly apply the Euclidean algorithm to infer the coefficients of a positive integer in polynomial representation, whose corresponding negative integer can be obtained with the help of the similar solution method of binary complement; secondly, the coefficients are respectively mapped into from mod p to mod the n-th power of p laye
2021-02-22 09:07:45 393KB distance measure; p-adic; metric
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