Results 41 to 50 of about 18,832 (283)

Human Motion Prediction Based on Space-Time-Separable Graph Convolutional Network

IEEE Access, 2023
Human motion prediction is a popular method to predict future motion sequences based on past sequences, which is widely used in human-computer interaction.
Rui Li, Duo He, Shiqiang Yang, An Yan, Xin Zeng, Dexin Li   +5 more
doaj   +1 more source

Identifying Experts in Community Question Answering Website Based on Graph Convolutional Neural Network

IEEE Access, 2020
High-quality answers, usually given by experts, play an important role in community question answering (CQA) websites. Therefore, experts in these websites are defined as those who provide high-quality answers.
Chen Liu, Yuchen Hao, Wei Shan, Zhihong Dai   +3 more
doaj   +1 more source

U-Net Greenhouse Sweet Cherry Image Segmentation Method Integrating PDE Plant Temporal Image Contrastive Learning and GCN Skip Connections

智慧农业
[Objective]Within the field of plant phenotyping feature extraction, the accurate delineation of small targets boundaries and the adequate recovery of spatial details during upsampling operations have long been recognized as significant obstacles ...
HU Lingyan, GUO Ruiya, GUO Zhanjun, XU Guohui, GAI Rongli, WANG Zumin, ZHANG Yumeng, JU Bowen, NIE Xiaoyu   +8 more
doaj   +1 more source

Comparative analysis of the EGFR, HER2, c-MYC, and MET variations in colorectal cancer determined by three different measures: gene copy number gain, amplification status and the 2013 ASCO/CAP guideline criterion for HER2 testing of breast cancer

Journal of Translational Medicine, 2017
Background The purpose of this study was to explore gene copy number (GCN) variation of EGFR, HER2, c-MYC, and MET in patients with primary colorectal cancer (CRC). Methods Dual-colour silver-enhanced in situ hybridization was performed in tissue samples
Yoonjin Kwak, Sumi Yun, Soo Kyung Nam, An Na Seo, Kyu Sang Lee, Eun Shin, Heung-Kwon Oh, Duck Woo Kim, Sung Bum Kang, Woo Ho Kim, Hye Seung Lee   +10 more
doaj   +1 more source

SVD-GCN

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
With the tremendous success of Graph Convolutional Networks (GCNs), they have been widely applied to recommender systems and have shown promising performance. However, most GCN-based methods rigorously stick to a common GCN learning paradigm and suffer from two limitations: (1) the limited scalability due to the high computational cost and slow ...
Shaowen Peng, Kazunari Sugiyama, Tsunenori Mine   +2 more
openaire   +2 more sources

Alkaline hydrogen evolution on CO-M@gCN dual-atom catalysts: insights from first-principles calculations

Tạp chí Khoa học và Công nghệ
Dual-atom catalysts (DACs) offer unique opportunities for enhancing electrocatalytic performance through synergistic metal interactions. Herein, we employ spin-polarized density functional theory to investigate Co-M DACs (M = Cr, Mn, Fe, Co, Ni, Cu, Pd ...
Tran Thi Kim Cuc, Thuy T. T. Duong, Ho Van Binh, Tien B. Tran, Thi H. Ho, Bich-Tram Truong Le, Dang Kim Hoang, Viet Q. Bui   +7 more
doaj   +1 more source

Synergistic effect of Ag/CuO composites on g-C3N4 nanosheets towards the visible-light active photocatalytic degradation of substituted benzoic acids in novel Ag/CuO@gCN heterojunction composites

Results in Chemistry, 2023
Advanced oxidation processes (AOPs) with heterojunction-based composites have been shown to be effective for a variety of water and/or wastewater treatments.
Marri Pradeep Kumar, Dasari Ayodhya
doaj   +1 more source

Bert-GCN: multi-sensors network prediction

, 2022
With the application of neural network technologies such as GCN and GRU in sensor networks, the accuracy and robustness of multi-sensor prediction have been greatly improved. GCN effectively uses the spatial characteristics of the sensor network, and GRU
Yang Cong, Peng Liu, Yuheng Xu, Zhuang Li   +3 more
core   +1 more source

Densely connected GCN model for motion prediction [PDF]

, 2020
© 2020 The Authors. Computer Animation and Virtual Worlds published by John Wiley & Sons, Ltd. Human motion prediction is a fundamental problem in understanding human natural movements.
Jianjun Zhang, Wang, Li, Fangde Liu, Iulian Poiana, Sebastian, Sebastian Iulian Poiana, Liu, Fangde, Iulian Poiana, S., Xiaosong Yang, Liu, Y., Wang, L., Li, Yanran, Lingteng Qiu, Qiu, Lingteng, Li Wang, Zhang, Jianjun, Zhang, Jian J., Qiu, L., Wang, Zhao, Wang, Z., Zhao Wang, Yang, Xiaosong, Liu, F., Yanran Li   +22 more
core   +1 more source

Graph Neural Networks for Malware Classification: Comparing Graph-Structured and Sequence-Based Representations

Iraqi Journal for Computers and Informatics
Malware detection is one of the most important cybersecurity issues because the traditional signature-based methods cannot resist polymorphic threats and obfuscated ones.
Meer Twana Qadir, Saman Mirza Abdullah
doaj   +1 more source