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Published in 2021 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22596
Abstract: Multiple kernel clustering (MKC) methods aim at integrating an optimal partition from a set of precalculated kernel matrices. Though achieving success in various applications, we observe that existing MKC methods: (i) lack of representation flexibility;…
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Keywords:
local graph;
kernel clustering;
multiple kernel;
graph ... See more keywords
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Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.07.082
Abstract: Vehicle re-identification is an important computer vision task where the objective is to identify a specific vehicle among a set of vehicles seen at various viewpoints. Recent methods based on deep learning utilize a global…
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Keywords:
vehicle;
vehicle identification;
local graph;
graph ... See more keywords
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3
Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3263852
Abstract: Exploiting global factors and embedding them directly into local graphs in point clouds are challenging due to dense points and irregular structure. To accomplish this goal, we propose a novel end-to-end trainable graph attention network…
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Keywords:
attention network;
graph;
local graph;
point ... See more keywords
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Published in 2021 at "IEEE/ACM Transactions on Computational Biology and Bioinformatics"
DOI: 10.1109/tcbb.2019.2936851
Abstract: The tracking of densely packed plant cells across microscopy image sequences is very challenging, because their appearance change greatly over time. A local graph matching algorithm was proposed to track such cells by exploiting the…
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Keywords:
local graph;
image sequences;
cell;
graph matching ... See more keywords