Spectral Graph Partitioning Based on a Random Walk Diffusion Similarity Measure

2010 ◽  
pp. 667-676 ◽  
Author(s):  
Xi Li ◽  
Weiming Hu ◽  
Zhongfei Zhang ◽  
Yang Liu
Keyword(s):  
Random Walk ◽  
Similarity Measure ◽  
Graph Partitioning ◽  
Spectral Graph ◽  
Spectral Graph Partitioning

FINAL VERSION.pdf

2019 ◽  
Author(s):  
Nasir Saeed ◽  
Mohamed-Slim Alouini ◽  
Tareq Y. Al-Naffouri
Keyword(s):  
Graph Partitioning ◽  
Three Dimensional ◽  
Smart Objects ◽  
Localization Technique ◽  
Optical Internet ◽  
Spectral Graph ◽  
Accurate Localization ◽  
Spectral Graph Partitioning ◽  
Link Connectivity

<div>Localization is a fundamental task for optical internet</div><div>of underwater things (O-IoUT) to enable various applications</div><div>such as data tagging, routing, navigation, and maintaining link connectivity. The accuracy of the localization techniques for OIoUT greatly relies on the location of the anchors. Therefore, recently localization techniques for O-IoUT which optimize the anchor’s location are proposed. However, optimization of anchors location for all the smart objects in the network is not a useful solution. Indeed, in a network of densely populated smart objects, the data collected by some sensors are more valuable than the data collected from other sensors. Therefore, in this paper, we propose a three-dimensional accurate localization technique by optimizing the anchor’s location for a set of smart objects. Spectral graph partitioning is used to select the set of valuable</div><div>sensors.</div>

Efficient nuclei segmentation based on spectral graph partitioning

2016 ◽  
Author(s):  
Gwo Giun Chris Lee ◽  
Shi-Yu Hung ◽  
Tai-Ping Wang ◽  
Chun-Fu Richard Chen ◽  
Chi-Kuang Sun ◽  
...  
Keyword(s):  
Graph Partitioning ◽  
Nuclei Segmentation ◽  
Spectral Graph ◽  
Spectral Graph Partitioning

FINAL VERSION.pdf

2019 ◽  
Author(s):  
Nasir Saeed ◽  
Mohamed-Slim Alouini ◽  
Tareq Y. Al-Naffouri
Keyword(s):  
Graph Partitioning ◽  
Three Dimensional ◽  
Smart Objects ◽  
Localization Technique ◽  
Optical Internet ◽  
Spectral Graph ◽  
Accurate Localization ◽  
Spectral Graph Partitioning ◽  
Link Connectivity

<div>Localization is a fundamental task for optical internet</div><div>of underwater things (O-IoUT) to enable various applications</div><div>such as data tagging, routing, navigation, and maintaining link connectivity. The accuracy of the localization techniques for OIoUT greatly relies on the location of the anchors. Therefore, recently localization techniques for O-IoUT which optimize the anchor’s location are proposed. However, optimization of anchors location for all the smart objects in the network is not a useful solution. Indeed, in a network of densely populated smart objects, the data collected by some sensors are more valuable than the data collected from other sensors. Therefore, in this paper, we propose a three-dimensional accurate localization technique by optimizing the anchor’s location for a set of smart objects. Spectral graph partitioning is used to select the set of valuable</div><div>sensors.</div>

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