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Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-07897-4
Abstract: Accurate climate predictions are essential for agriculture, urban planning, and disaster management. Traditional forecasting methods often struggle with regional accuracy, computational demands, and scalability. This study proposes a Transformer-based deep learning model for daily temperature…
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Keywords:
climate;
transformer based;
forecasting;
graph ... See more keywords
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Published in 2023 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2023.3270739
Abstract: Predicting the multimodal future motions of neighboring agents is essential for an autonomous vehicle to navigate complex scenarios. It is challenging as the motion of an agent is affected by the complex interaction among itself,…
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Keywords:
map adaptive;
future motions;
hierarchical graph;
graph ... See more keywords
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Published in 2025 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2024.3497805
Abstract: Three significant challenges have been limiting the stable palmprint recognition via mobile devices: 1) rotations and unconsensus scales of the unconstrait hand; 2) noises generated in the open imaging environments; and 3) low quality images…
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Keywords:
recognition;
palmprint recognition;
multi view;
palmprint ... See more keywords
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Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2022.3177647
Abstract: Recently, deep dictionary learning (DDL) has aroused attention due to its abilities of learning multiple different dictionaries and extracting multi-level abstract feature representations for samples. It has been applied to many intelligent recognition tasks, such…
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Keywords:
hierarchical graph;
dictionary learning;
deep collaborative;
collaborative dictionary ... See more keywords
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Published in 2023 at "IEEE transactions on medical imaging"
DOI: 10.1109/tmi.2023.3273236
Abstract: Pathological primary tumor (pT) stage focuses on the infiltration degree of the primary tumor to surrounding tissues, which relates to the prognosis and treatment choices. The pT staging relies on the field-of-views from multiple magnifications…
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Keywords:
structure aware;
hierarchical graph;
instance learning;
graph based ... See more keywords
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Published in 2022 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2022.3203703
Abstract: Node classification and graph classification are two graph learning problems that predict the class label of a node and the class label of a graph respectively. A node of a graph usually represents a real-world…
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Keywords:
network;
semi supervised;
graph;
hierarchical graph ... See more keywords
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Published in 2022 at "IEEE transactions on visualization and computer graphics"
DOI: 10.1109/tvcg.2022.3218028
Abstract: Automatic tooth alignment target prediction is vital in shortening the planning time of orthodontic treatments and aligner designs. Generally, the quality of alignment targets greatly depends on the experience and ability of dentists and has…
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Keywords:
hierarchical graph;
network;
landmark constraints;
tooth alignment ... See more keywords
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Published in 2022 at "Computer Graphics Forum"
DOI: 10.1111/cgf.14643
Abstract: We propose a hierarchical graph for learning physics and a novel way to handle obstacles. The finest level of the graph consist of the particles itself. Coarser levels consist of the cells of sparse grids…
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Keywords:
physics hierarchical;
network;
physics;
learning physics ... See more keywords
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Published in 2020 at "Frontiers in Molecular Biosciences"
DOI: 10.3389/fmolb.2020.599059
Abstract: For the investigation of protein-ligand interaction patterns, the current accessibility of a wide variety of sampling methods allows quick access to large-scale data. The main example is the intensive use of molecular dynamics simulations applied…
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Keywords:
representation pharmacophore;
graph representation;
hierarchical graph;
pharmacophore models ... See more keywords
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Published in 2022 at "Entropy"
DOI: 10.3390/e24111691
Abstract: Recently, with the rise of deep learning, text classification techniques have developed rapidly. However, the existing work usually takes the entire text as the modeling object and pays less attention to the hierarchical structure within…
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Keywords:
attention network;
graph;
hierarchical graph;
attention ... See more keywords