A Replacement Algorithm of Non-Maximum Suppression Base on Graph Clustering
نویسندگان
چکیده
منابع مشابه
Finding Community Base on Web Graph Clustering
Search Pointers organize the main part of the application on the Internet. However, because of Information management hardware, high volume of data and word similarities in different fields the most answers to the user s’ questions aren`t correct. So the web graph clustering and cluster placement in corresponding answers helps user to achieve his or her intended results. Community (web communit...
متن کاملfinding community base on web graph clustering
search pointers organize the main part of the application on the internet. however, because of information management hardware, high volume of data and word similarities in different fields the most answers to the user s’ questions aren`t correct. so the web graph clustering and cluster placement in corresponding answers helps user to achieve his or her intended results. community (web communit...
متن کاملFinding community base on web graph clustering
Search Pointers organize the main part of the application on the Internet. However, because of Information management hardware, high volume of data and word similarities in different fields the most answers to the user s’ questions aren`t correct. So the web graph clustering and cluster placement in corresponding answers helps user to achieve his or her intended results. Community (web communit...
متن کاملDeciding Graph non-Hamiltonicity via a Closure Algorithm
We present a matching and LP based heuristic algorithm that decides graph non-Hamiltonicity. Each of the n! Hamilton cycles in a complete directed graph on n + 1 vertices corresponds with each of the n! n-permutation matrices P, such that pu,i = 1 if and only if the ith arc in a cycle enters vertex u, starting and ending at vertex n + 1. A graph instance (G) is initially coded as exclusion set ...
متن کاملA Convnet for Non-maximum Suppression
Non-maximum suppression (NMS) is used in virtually all state-of-the-art object detection pipelines. While essential object detection ingredients such as features, classifiers and proposal methods have been extensively researched it it surprising how little work has aimed to systematically address NMS. The de-facto standard for NMS is based on greedy clustering with a fixed distance threshold, w...
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ژورنال
عنوان ژورنال: ITM Web of Conferences
سال: 2017
ISSN: 2271-2097
DOI: 10.1051/itmconf/20171205006