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Prim's algorithm

About: Prim's algorithm is a research topic. Over the lifetime, 775 publications have been published within this topic receiving 17971 citations. The topic is also known as: DJP algorithm & Jarník algorithm.


Papers
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Journal ArticleDOI
TL;DR: This article combines a region growing algorithm based on simple surface fitting and morphological reconstruction to initially segment sports actions and improves the prim algorithm, and combines an optimized watershed segmentation framework to construct a new energy function using the T-prim minimum spanning tree algorithm.
Abstract: Aiming at the situation that the motion recognition of sports athletes is interfered by a variety of factors and the recognition results are not ideal, this paper uses the maximum spanning tree algorithm as the model basis to use machine learning ideas to construct a sports player motion recognition model based on the maximum spanning tree algorithm. Moreover, this article combines a region growing algorithm based on simple surface fitting and morphological reconstruction to initially segment sports actions. After that, this paper improves the prim algorithm, and combines an optimized watershed segmentation framework to construct a new energy function using the T-prim minimum spanning tree algorithm proposed in this paper. The constructed T-prim tree is combined with this optimized watershed segmentation framework to complete the segmentation of sports images.Finally, this paper designs experiments to verify the actual effect of the method proposed in this paper. It can be seen from the research results that the model constructed in this paper basically achieves the expected goal.

1 citations

Proceedings ArticleDOI
Jiaru Wang1, Ziyi Wan1, Jiankang Song1, Yanze Huang1, Yuhang Lin1, Limei Lin1 
19 Nov 2021
TL;DR: Kruskal and Prim algorithms are used to model the linear programming of the minimum spanning tree and their anonymity feasibility is verified.
Abstract: Privacy protection of individual users in social networks is becoming more and more important, thus it requires effective anonymization techniques. In this paper, we use Kruskal and Prim algorithms to model the linear programming of the minimum spanning tree. Finally, we execute the experiments on the number of anonymity solutions and time with different edge weights to analyze the Kruskal algorithm and Prim algorithm to verify their anonymity feasibility.

1 citations

Journal Article
Zhang Jing1
TL;DR: The improved algorithm and simple algorithm are used to solve the cable television network respectively, and the contrast of their results shows the effectiveness of the improved genetic algorithm.
Abstract: The concept of minimum spanning tree is introduced and its limitation is analyzed The cost of the node degree is considered and accordingly the concept of generalized minimum spanning tree (GMST) is presented Genetic algorithm is used to solve GMST To correct the shortcomings of simple genetic algorithm in this problem, a self-adjusting mutation operator and a hybrid selection strategy are designed Through the modelling and simulation of a cable television network, the applicability of GMST is proved Finally, the improved algorithm and simple algorithm are used to solve the cable television network respectively, and the contrast of their results shows the effectiveness of the improved genetic algorithm

1 citations

Journal Article
TL;DR: It is suggested to solve the full bottleneck Steiner tree problem is to find a tree S from the undirected graph G, with all the vertices in the given points being leaves and the weights of the maximum edges being minimum.
Abstract: It is suggested to solve the full bottleneck Steiner tree problem is to find a tree S from the undirected graph G,with all the vertices in the given points being leaves and the weights of the maximum edges being minimumAfter giving out the definition of full bottleneck Steiner tree,we use methed of transforming,decomposing and combining to give out a polynominal algorithm for solving the problemComplexity of time in that algorithm is given,and examples are presented to show the validity of the algorithm

1 citations

Journal Article
TL;DR: Experiment indicated that the method can keep the boundary of region while merging "over-segmentation" regions quickly and effectively, and it is effective for remote sensing images of complex and large size.
Abstract: To solve the problem of over-segmentation caused by noise when applying watershed segmentation based on morpho-logy,a new regions merging method is proposed.Based on the minimum spanning tree algorithm(prim,kruskal,boruvka),segmented region is regarded as the vertex of a graph,adjacent regions are regarded as the edges whose weight is determined by the difference between the segmented region and adjacent region,regions merging is completed by setting the appropriate threshold and iteration times.Experiment indicated that the method can keep the boundary of region while merging"over-segmentation" regions quickly and effectively,and it is effective for remote sensing images of complex and large size.

1 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20232
20224
202113
20208
201920
201815