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Published in 2019 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-019-7518-3
Abstract: Graph construction has attracted increasing interest in recent years due to its key role in many dimensionality reduction (DR) algorithms. On the other hand, our previous study shows that the Local-Binary-Pattern Image (LBPI) representation is…
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Keywords:
discriminant graph;
graph;
graph construction;
dimensionality reduction ... See more keywords
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Published in 2019 at "Neuroimage"
DOI: 10.1016/j.neuroimage.2019.05.052
Abstract: Structural brain networks derived from diffusion magnetic resonance imaging data have been used extensively to describe the human brain, and graph theory has allowed quantification of their network properties. Schemes used to construct the graphs…
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Keywords:
network;
topology;
graph construction;
brain ... See more keywords
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Published in 2020 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.0c00503
Abstract: We present the graph-based molecule software Molassembler for building organic and inorganic molecules. Molassembler provides algorithms for the construction of molecules built from any set of elements from the periodic table. In particular, poly-nuclear transition…
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Keywords:
molecular graph;
molassembler molecular;
construction;
molecules molassembler ... See more keywords
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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2895865
Abstract: The quantitation of morphology information of X-ray angiography image has an important value in the diagnosis of coronary artery disease. This paper proposes an automatic morphology estimation method by using directed graph construction for X-ray…
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Keywords:
graph construction;
directed graph;
quantitation vascular;
vessel ... See more keywords
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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2939539
Abstract: Dimensionality reduction is a fundamental task in the field of data mining and machine learning. In many scenes, examples in high-dimensional space usually lie on low-dimensional manifolds; thus, learning the low-dimensional embedding is important. Some…
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Keywords:
neighbors based;
graph construction;
dimensionality reduction;
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Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3221150
Abstract: Many graph construction methods for clustering cannot consider both local and global data structures in the construction of initial graph. Meanwhile, redundant features or even outliers and data with important characteristics are addressed equally in…
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Keywords:
graph construction;
graph;
representation graph;
representation ... See more keywords
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Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2021.3136161
Abstract: Graph learning-based algorithms are becoming the prevalent traffic prediction solutions due to their capability of exploiting non-Euclidean spatial-temporal traffic data correlation. However, current predictors primarily employ heuristically constructed static traffic graphs in forecasting, which may…
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Keywords:
traffic;
traffic prediction;
graph construction;
data driven ... See more keywords
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Published in 2017 at "International Journal of Genomics"
DOI: 10.1155/2017/6120980
Abstract: Background The rapid advancement of sequencing technologies has made it possible to regularly produce millions of high-quality reads from the DNA samples in the sequencing laboratories. To this end, the de Bruijn graph is a…
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Keywords:
bruijn graph;
graph;
graph construction;
genome assembly ... See more keywords