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Published in 2017 at "Journal of Computational Chemistry"
DOI: 10.1002/jcc.24664
Abstract: We present an efficient density‐based adaptive‐resolution clustering method APLoD for analyzing large‐scale molecular dynamics (MD) trajectories. APLoD performs the k‐nearest‐neighbors search to estimate the density of MD conformations in a local fashion, which can group…
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Keywords:
molecular dynamics;
density;
dynamics trajectories;
density based ... See more keywords
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Published in 2018 at "International Journal of Machine Learning and Cybernetics"
DOI: 10.1007/s13042-017-0648-x
Abstract: Density peaks clustering (DPC) algorithm is a novel clustering algorithm based on density. It needs neither iterative process nor more parameters. However, it cannot effectively group data with arbitrary shapes, or multi-manifold structures. To handle…
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Keywords:
using geodesic;
density;
peaks clustering;
geodesic distances ... See more keywords
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Published in 2019 at "Artificial intelligence in medicine"
DOI: 10.1016/j.artmed.2019.03.002
Abstract: Clustering white matter (WM) tracts from diffusion tensor imaging (DTI) is primarily important for quantitative analysis on pediatric brain development. A recently developed algorithm, density peaks (DP) clustering, demonstrates great robustness to the complex structural…
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Keywords:
density peaks;
density;
peaks clustering;
analysis ... See more keywords
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Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2017.05.072
Abstract: Abstract Having a multitude of unlabeled data and few labeled ones is a common problem in many practical applications. A successful methodology to tackle this problem is self-training semi-supervised classification. In this paper, we introduce…
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Keywords:
semi supervised;
supervised classification;
self training;
training semi ... See more keywords
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Published in 2019 at "Physica A: Statistical Mechanics and its Applications"
DOI: 10.1016/j.physa.2018.09.002
Abstract: The Density Peaks Clustering (DPC) algorithm, published in Science, is a novel density-based clustering approach. Gravitation-based Density Peaks Clustering (GDPC) algorithm, inherited the advantages of DPC, is an improved algorithm. GDPC is able to detect…
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Keywords:
dpc;
density peaks;
gravitation;
density ... See more keywords
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Published in 2022 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btac021
Abstract: MOTIVATION Density Peaks is a widely spread clustering algorithm that has been previously applied to Molecular Dynamics simulations. Its conception of cluster centers as elements displaying both a high density of neighbors and a large…
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Keywords:
density peaks;
density;
molecular dynamics;
rcdpeaks memory ... See more keywords
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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2927308
Abstract: Density peaks clustering is a novel and efficient density-based clustering algorithm. However, the problem of the sensitive information leakage and the associated security risk with the applications of clustering methods is rarely considered. To address…
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Keywords:
density peaks;
density;
shared near;
near neighbors ... See more keywords
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Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3006069
Abstract: Density peaks clustering (DPC) algorithm is a novel density-based clustering algorithm, which is simple and efficient, is not necessary to specify the number of clusters in advance, and can find any nonspherical class clusters. However,…
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Keywords:
density peaks;
clustering algorithm;
density;
nearest neighbors ... See more keywords
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Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3190958
Abstract: Density peaks clustering has become a nova of clustering algorithm because of its simplicity and practicality. However, there is one main drawback: it is time-consuming due to its high computational complexity. Herein, a density peaks…
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Keywords:
density peaks;
density;
peaks clustering;
tex math ... See more keywords
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Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3227936
Abstract: Density peaks clustering (DPC) is a simple and efficient density-based clustering algorithm without complex iterative procedures. However, DPC needs to manually choose clustering centers via a decision graph, which often can’t identify real centers and…
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Keywords:
density peaks;
diffusion;
density;
peaks clustering ... See more keywords
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Published in 2019 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2019.2912989
Abstract: Robust detection of infrared small target is still a challenge due to the diversity and complexity of the background. In this letter, we propose a novel detection approach based on density peaks searching and maximum-gray…
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Keywords:
density peaks;
small target;
density;
infrared small ... See more keywords