Results 11 to 20 of about 22,751 (263)

GCN-PTO.xlsx

open access: yes, 2023
Towards Sufficient Power-Traffic Coordination: GCN-based Prediction of Spatial-Temporal EV Charging ...
浩 成 (15741326)
openaire   +2 more sources

MLC-GCN: Multi-Level Generated Connectome Based GCN for AD Analysis [PDF]

open access: yesCoRR
Alzheimer's Disease (AD) is a currently incurable neurodegeneartive disease. Accurately detecting AD, especially in the early stage, represents a high research priority. AD is characterized by progressive cognitive impairments that are related to alterations in brain functional connectivity (FC).
Wenqi Zhu, Yinghua Fu, Ze Wang
core   +4 more sources

Mesh evaluation method for shell elements using graph convolutional network

open access: yesNihon Kikai Gakkai ronbunshu, 2023
Finite element mesh quality, which affects analysis accuracy and computational cost, is usually determined based on the designer's experience. In this study, we propose a GCN (Graph Convolutional network)-based method for evaluating the quality of ...
Yujin YOKOI   +2 more
doaj   +1 more source

Multi-Semantic Alignment Graph Convolutional Network

open access: yesConnection Science, 2022
Graph Convolutional Network (GCN) is a powerful emerging deep learning technique for learning graph data. However, there are still some challenges for GCN. For example, the model is shallow; the performance is poor when labelled nodes are severely scarce.
Jisheng Qin   +3 more
doaj   +1 more source

GP-GCN: Global features of orthogonal projection and local dependency fused graph convolutional networks for aspect-level sentiment classification

open access: yesConnection Science, 2022
Aspect-level sentiment classification, a significant task of fine-grained sentiment analysis, aims to identify the sentimental information expressed in each aspect of a given sentence The existing methods combine global features and local structures to ...
Subo Wei   +4 more
doaj   +1 more source

E-GCN: graph convolution with estimated labels [PDF]

open access: yes, 2021
Graph Convolutional Network (GCN) has been commonly applied for semi-supervised learning tasks. How-ever, the established GCN frequently only considers the given labels in the topology optimization, which may not deliver the best performance for semi ...
Zeng, Xiaoqin   +3 more
core   +1 more source

TS-GCN: A novel tumor segmentation method integrating transformer and GCN

open access: yesMathematical Biosciences and Engineering, 2023
<abstract><p>As one of the critical branches of medical image processing, the task of segmentation of breast cancer tumors is of great importance for planning surgical interventions, radiotherapy and chemotherapy. Breast cancer tumor segmentation faces several challenges, including the inherent complexity and heterogeneity of breast tissue,
Haiyan Song   +3 more
openaire   +3 more sources

Highly Mesoporous g-C3N4 with Uniform Pore Size Distribution via the Template-Free Method to Enhanced Solar-Driven Tetracycline Degradation

open access: yesNanomaterials, 2021
A highly mesoporous graphitic carbon nitride g-C3N4 (GCN) has been produced by a template-free method and effectively photodegrade tetracycline (TC) antibiotic under solar light irradiation. The mesoporous GCN (GCN-500) greatly improves the photoactivity
Bao Lee Phoon   +4 more
doaj   +1 more source

A^2-GCN: An Attribute-aware Attentive GCN Model for Recommendation

open access: yesCoRR, 2020
As important side information, attributes have been widely exploited in the existing recommender system for better performance. In the real-world scenarios, it is common that some attributes of items/users are missing (e.g., some movies miss the genre data).
Fan Liu 0008   +4 more
openaire   +2 more sources

Heterogeneous EGFR gene copy number increase is common in colorectal cancer and defines response to anti-EGFR therapy. [PDF]

open access: yesPLoS ONE, 2014
Anti-EGFR therapy is commonly used to treat colorectal cancer (CRC), although only a subset of patients benefit from the treatment. While KRAS mutation predicts non-responsiveness, positive predictive markers are not in clinical practice.
Annika Ålgars   +8 more
doaj   +1 more source

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