Results 81 to 90 of about 4,990,305 (257)

Learning Graph Convolutional Network for Blind Mesh Visual Quality Assessment

, 2021
This paper proposes a new method for blind mesh visual quality assessment (MVQA) based on a graph convolutional network. For that, we address the node classification problem to predict the perceived visual quality. First, two matrices representing the 3D
Longin Jan Latecki, Mohammed El Hassouni, Chetouani, Aladine, Hassouni, Mohammed El, Latecki, Longin Jan, Ilyass Abouelaziz, Abouelaziz, Ilyass, Cherifi, Hocine, Hocine Cherifi, Aladine Chetouani   +9 more
core   +1 more source

DDSurfer: A Weakly‐Supervised Dual‐Stream Deep Learning Framework for Cortical Surface Reconstruction From Diffusion MRI

Advanced Science, EarlyView.
DDSurfer reconstructs cortical surfaces directly from diffusion MRI without requiring T1‐weighted scans. By fusing complementary microstructural features and learning diffeomorphic deformations, it efficiently generates accurate white matter and pial surfaces, improving geometric fidelity and morphometric reliability across datasets for robust surface ...
Chengjin Li, Wei Zhang, Xi Zhu, Yuqian Chen, Nir A. Sochen, Jarrett Rushmore, Carl‐Fredrik Westin, Yogesh Rathi, Lauren J. O'Donnell, Ofer Pasternak, Fan Zhang   +10 more
wiley   +1 more source

Multi-channel based edge-learning graph convolutional network

Dianxin kexue, 2022
Usually the edges of the graph contain important information of the graph.However, most of deep learning models for graph learning, such as graph convolutional network (GCN) and graph attention network (GAT), do not fully utilize the characteristics of ...
Shuai YANG, Ruiqin WANG, Hui MA
doaj   +2 more sources

Tensor Graph Convolutional Network for Dynamic Graph Representation Learning [PDF]

Dynamic graphs (DG) describe dynamic interactions between entities in many practical scenarios. Most existing DG representation learning models combine graph convolutional network and sequence neural network, which model spatial-temporal dependencies ...
Yuan, Ye, Wang, Ling
core   +1 more source

Cold-Start Traffic State Forecasting at Unseen Sensor Locations via Support-Conditioned Meta-Graph Learning

Sensors
Traffic sensors provide real-time measurements of current traffic conditions, whereas traffic management applications require forecasts of future traffic speed or flow.
Can Wang, Zhiyu Wang, Weijie Wang, Jing Gan, Yanni Ju   +4 more
doaj   +1 more source

Improved GCN Model for Inexact Graph Matching

Jisuanji kexue yu tansuo, 2020
Aiming at the problem of mining the features of topology nodes deficiently in the existing inexact graph matching, this paper proposes an improved graph convolutional network (GCN) model for inexact graph matching. Firstly, considering that the selecting
LI Changhua, CUI Liyang, LI Zhijie
doaj   +1 more source

Enhancing Super‐Resolution Spatial Transcriptomics Data by Transfer Learning

Advanced Science, EarlyView.
SpotZoomer employs a transfer‐learning‐based strategy to enhance the resolution of Visium data by leveraging available high‐resolution priors. The resulting super‐resolved maps enable sharper delineation of cell boundaries and more precise inference of cell–cell communication patterns that would otherwise remain obscured at native resolution.
Xiaoyu Li, Lihua Zhang, Wenwen Min
wiley   +1 more source

A malware classification method based on directed API call relationships.

PLoS ONE
In response to the growing complexity of network threats, researchers are increasingly turning to machine learning and deep learning techniques to develop advanced models for malware detection.
Cuihua Ma, Zhenwan Li, Haixia Long, Anas Bilal, Xiaowen Liu   +4 more
doaj   +1 more source

Cancer‐Associated BCL‐2 Mutants Reveal Mechanisms Towards Venetoclax Resistance

Advanced Science, EarlyView.
Venetoclax (VEN) resistance in chronic lymphocytic leukemia arises from diverse BCL2 mutations. We map mechanisms contributing to VEN resistance across common BCL‐2 variants. G101V and D103Y reduce drug binding and increase sequestration of pro‐apoptotic proteins. V156D blocks VEN allosterically.
Jonas Aufdermauer, Ian de Ridder, Mahjoobeh Ehsani, Marasim Khan, Justin Kale, Lukas P. Frenzel, David Andrews, Spyridoula Karamanou, Ana J. Garcia‐Saez, Geert Bultynck   +9 more
wiley   +1 more source

Drug-induced liver injury prediction based on graph convolutional networks and toxicogenomics.

PLoS Computational Biology
Drug-induced liver injury is a leading cause of high attrition rates for both candidate drugs and marketed medications. Previous in silico models may not effectively utilize biological drug property information and often lack robust model validation.
Tong Xiao, Ying Liu, Kaimiao Hu, Kaimin Guo, Mengying Zhang, TingTing Wang, Weihua Lei, Wenjia Wang, Shuiping Zhou, Yunhui Hu, Ran Su   +10 more
doaj   +1 more source