An overview on density peaks clustering
X Wei, M Peng, H Huang, Y Zhou - Neurocomputing, 2023 - Elsevier
Density peaks clustering (DPC) algorithm is a new algorithm based on density clustering
analysis, which can quickly obtain the cluster centers by drawing the decision diagram by …
analysis, which can quickly obtain the cluster centers by drawing the decision diagram by …
Dynamic planning of bicycle stations in dockless public bicycle-sharing system using gated graph neural network
Benefiting from convenient cycling and flexible parking locations, the Dockless Public
Bicycle-sharing (DL-PBS) network becomes increasingly popular in many countries …
Bicycle-sharing (DL-PBS) network becomes increasingly popular in many countries …
Fast density peaks clustering algorithm based on improved mutual K-nearest-neighbor and sub-cluster merging
C Li, S Ding, X Xu, H Hou, L Ding - Information Sciences, 2023 - Elsevier
Density peaks clustering (DPC) has had an impact in many fields, as it can quickly select
centers and effectively process complex data. However, it also has low operational efficiency …
centers and effectively process complex data. However, it also has low operational efficiency …
Veriml: Enabling integrity assurances and fair payments for machine learning as a service
Machine Learning as a Service (MLaaS) allows clients with limited resources to outsource
their expensive ML tasks to powerful servers. Despite the huge benefits, current MLaaS …
their expensive ML tasks to powerful servers. Despite the huge benefits, current MLaaS …
SFKNN-DPC: Standard deviation weighted distance based density peak clustering algorithm
J Xie, X Liu, M Wang - Information Sciences, 2024 - Elsevier
DPC (Clustering by fast search and find of Density Peaks) algorithm and its variations
typically employ Euclidean distance, overlooking the diverse contributions of individual …
typically employ Euclidean distance, overlooking the diverse contributions of individual …
VDPC: Variational density peak clustering algorithm
The widely applied density peak clustering (DPC) algorithm makes an intuitive cluster
formation assumption that cluster centers are often surrounded by data points with lower …
formation assumption that cluster centers are often surrounded by data points with lower …
HCDC: A novel hierarchical clustering algorithm based on density-distance cores for data sets with varying density
QF Yang, WY Gao, G Han, ZY Li, M Tian, SH Zhu… - Information Systems, 2023 - Elsevier
Cluster analysis is a crucial data mining technology widely used in image segmentation,
language processing, and pattern recognition. Most existing clustering algorithms cannot …
language processing, and pattern recognition. Most existing clustering algorithms cannot …
Efficient face detection and tracking in video sequences based on deep learning
G Zheng, Y Xu - Information Sciences, 2021 - Elsevier
Video-based face detection and tracking technology has been widely used in video
surveillance, safe driving, and medical diagnosis. In video sequences, most existing face …
surveillance, safe driving, and medical diagnosis. In video sequences, most existing face …
DASECount: Domain-agnostic sample-efficient wireless indoor crowd counting via few-shot learning
Accurate indoor crowd counting (ICC) is a key enabler to many smart home/office
applications. Recent development of the WiFi-based ICC technology relies on detecting the …
applications. Recent development of the WiFi-based ICC technology relies on detecting the …
A new density peak clustering algorithm based on cluster fusion strategy
F Li, M Zhou, S Li, T Yang - Ieee Access, 2022 - ieeexplore.ieee.org
When the density peak clustering algorithm deals with complex datasets and the problem of
multiple density peaks in the same cluster, the subjectively selected cluster centers are not …
multiple density peaks in the same cluster, the subjectively selected cluster centers are not …