Results 11 to 20 of about 13,926 (236)
Feature recommendation strategy for graph convolutional network
Connection Science, 2022 Graph Convolutional Network (GCN) is a new method for extracting, learning, and inferencing graph data that builds an embedded representation of the target node by aggregating information from neighbouring nodes.
Jisheng Qin +3 more
doaj +1 more source
Mesh evaluation method for shell elements using graph convolutional network
Nihon 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
Connection 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
Connection 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
Nanomaterials, 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
TS-GCN: A novel tumor segmentation method integrating transformer and GCN
Mathematical 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
Heterogeneous EGFR gene copy number increase is common in colorectal cancer and defines response to anti-EGFR therapy. [PDF]
PLoS 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
A^2-GCN: An Attribute-aware Attentive GCN Model for Recommendation
CoRR, 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
Frontiers in Genetics, 2023 Spatially resolved transcriptomics (SRT) provides an unprecedented opportunity to investigate the complex and heterogeneous tissue organization. However, it is challenging for a single model to learn an effective representation within and across spatial ...
Xinxing Li +4 more
doaj +1 more source
Atoms, 2023 In this work, a group-11 metal nanoparticle-embedded, graphitic carbon nitride-based, resistive-type sensor was developed for room temperature acetone sensing.
Nihal +5 more
doaj +1 more source