Articles with "density peaks" as a keyword



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Adaptive partitioning by local density‐peaks: An efficient density‐based clustering algorithm for analyzing molecular dynamics trajectories

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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… read more here.

Keywords: molecular dynamics; density; dynamics trajectories; density based ... See more keywords
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Density peaks clustering using geodesic distances

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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… read more here.

Keywords: using geodesic; density; peaks clustering; geodesic distances ... See more keywords
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Fast density-peaks clustering for registration-free pediatric white matter tract analysis

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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… read more here.

Keywords: density peaks; density; peaks clustering; analysis ... See more keywords
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Self-training semi-supervised classification based on density peaks of data

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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… read more here.

Keywords: semi supervised; supervised classification; self training; training semi ... See more keywords
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DPC-LG: Density peaks clustering based on logistic distribution and gravitation

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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… read more here.

Keywords: dpc; density peaks; gravitation; density ... See more keywords
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RCDPeaks: memory-efficient density peaks clustering of long molecular dynamics

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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… read more here.

Keywords: density peaks; density; molecular dynamics; rcdpeaks memory ... See more keywords
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Differential Privacy-Preserving Density Peaks Clustering Based on Shared Near Neighbors Similarity

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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… read more here.

Keywords: density peaks; density; shared near; near neighbors ... See more keywords
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Effective Density Peaks Clustering Algorithm Based on the Layered K-Nearest Neighbors and Subcluster Merging

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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,… read more here.

Keywords: density peaks; clustering algorithm; density; nearest neighbors ... See more keywords
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A Density Peaks Clustering Algorithm With Sparse Search and K-d Tree

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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… read more here.

Keywords: density peaks; density; peaks clustering; tex math ... See more keywords
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Density Peaks Clustering Based on Potential Model and Diffusion Strength

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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… read more here.

Keywords: density peaks; diffusion; density; peaks clustering ... See more keywords
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Infrared Small Target Detection by Density Peaks Searching and Maximum-Gray Region Growing

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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… read more here.

Keywords: density peaks; small target; density; infrared small ... See more keywords