Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Xiyu Liu"'
Publikováno v:
Applied Sciences
Volume 13
Issue 4
Pages: 2293
Volume 13
Issue 4
Pages: 2293
Density Peaks Clustering (DPC) has recently received much attention in many fields by reason of its simplicity and efficiency. Nevertheless, empirical studies have shown that DPC has some shortfalls: (i) similarity measurement based on Euclidean dist
Publikováno v:
IEEE Access. 10:114642-114656
Publikováno v:
IEEE Access. 10:128604-128621
Publikováno v:
Expert Systems with Applications. 215:119234
Publikováno v:
Mathematical Problems in Engineering, Vol 2020 (2020)
An extended clustering membrane system using a cell-like P system with active membranes based on particle swarm optimization (PSO), named PSO-CP, is designed, developed, implemented, and tested. The purpose of PSO-CP is to solve clustering problems.
Publikováno v:
IEEE Access, Vol 8, Pp 154502-154517 (2020)
Consensus clustering algorithm, which integrates several clustering results obtained by common algorithms, can find a better result that is independent on parameter settings. However, this kind of algorithm is often designed based on simple, such as
Publikováno v:
IEEE Access, Vol 8, Pp 113900-113917 (2020)
Density Peaks Clustering (DPC) is a density-based clustering algorithm that has the advantage of not requiring clustering parameters and detecting non-spherical clusters. The density peaks algorithm obtains the actual cluster center by inputting the
Publikováno v:
Journal of Computational Methods in Sciences and Engineering. 19:603-617
Publikováno v:
IEEE Access, Vol 7, Pp 84565-84579 (2019)
Clustering algorithms have attracted a lot of attentions recently in real-world applications. However, the traditional clustering algorithms still have plenty of defects which are not yet resolved. In this paper, a kernel-based intuitionistic fuzzy C
Autor:
Yuan Wang, Dengwang Li, Jie Xue, Shuo Yan, Xiyu Liu, Tingting Liu, Feng Qi, Hongyan Zhang, Jianhua Qu, Chenggong Qiu
Publikováno v:
IEEE Access, Vol 7, Pp 143058-143066 (2019)
Accurate segmentation of choroidal neovascularization (CNV) patterns is vital for precise lesion size quantification in age-related macular degeneration. In this paper, we develop a method for unsupervised and parallel segmentation of CNV in optical