Artigos de revistas sobre o tema "Graph Pooling and Convolution"
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Qin, Jian, Li Liu, Hui Shen e Dewen Hu. "Uniform Pooling for Graph Networks". Applied Sciences 10, n.º 18 (10 de setembro de 2020): 6287. http://dx.doi.org/10.3390/app10186287.
Texto completo da fonteYang, Xiaowen, Yanghui Wen, Shichao Jiao, Rong Zhao, Xie Han e Ligang He. "Point Cloud Segmentation Network Based on Attention Mechanism and Dual Graph Convolution". Electronics 12, n.º 24 (13 de dezembro de 2023): 4991. http://dx.doi.org/10.3390/electronics12244991.
Texto completo da fonteDiao, Qi, Yaping Dai, Jiacheng Wang, Xiaoxue Feng, Feng Pan e Ce Zhang. "Spatial-Pooling-Based Graph Attention U-Net for Hyperspectral Image Classification". Remote Sensing 16, n.º 6 (7 de março de 2024): 937. http://dx.doi.org/10.3390/rs16060937.
Texto completo da fonteMa, Zheng, Junyu Xuan, Yu Guang Wang, Ming Li e Pietro Liò. "Path integral based convolution and pooling for graph neural networks*". Journal of Statistical Mechanics: Theory and Experiment 2021, n.º 12 (1 de dezembro de 2021): 124011. http://dx.doi.org/10.1088/1742-5468/ac3ae4.
Texto completo da fonteLi, Shenhao, Zhichon Pan, Hongyi Li, Yue Xiao, Ming Liu e Xiaorui Wang. "Convergence criterion of power flow calculation based on graph neural network". Journal of Physics: Conference Series 2703, n.º 1 (1 de fevereiro de 2024): 012042. http://dx.doi.org/10.1088/1742-6596/2703/1/012042.
Texto completo da fonteGuo, Kan, Yongli Hu, Yanfeng Sun, Sean Qian, Junbin Gao e Baocai Yin. "Hierarchical Graph Convolution Network for Traffic Forecasting". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 1 (18 de maio de 2021): 151–59. http://dx.doi.org/10.1609/aaai.v35i1.16088.
Texto completo da fonteBachlechner, M., T. Birkenfeld, P. Soldin, A. Stahl e C. Wiebusch. "Partition pooling for convolutional graph network applications in particle physics". Journal of Instrumentation 17, n.º 10 (1 de outubro de 2022): P10004. http://dx.doi.org/10.1088/1748-0221/17/10/p10004.
Texto completo da fonteArsini, Lorenzo, Barbara Caccia, Andrea Ciardiello, Stefano Giagu e Carlo Mancini Terracciano. "Nearest Neighbours Graph Variational AutoEncoder". Algorithms 16, n.º 3 (6 de março de 2023): 143. http://dx.doi.org/10.3390/a16030143.
Texto completo da fonteCheung, Mark, John Shi, Oren Wright, Lavendar Y. Jiang, Xujin Liu e Jose M. F. Moura. "Graph Signal Processing and Deep Learning: Convolution, Pooling, and Topology". IEEE Signal Processing Magazine 37, n.º 6 (novembro de 2020): 139–49. http://dx.doi.org/10.1109/msp.2020.3014594.
Texto completo da fonteChen, Jiawang, e Zhenqiang Wu. "Learning Embedding for Signed Network in Social Media with Hierarchical Graph Pooling". Applied Sciences 12, n.º 19 (28 de setembro de 2022): 9795. http://dx.doi.org/10.3390/app12199795.
Texto completo da fonteTian, Luogeng, Bailong Yang, Xinli Yin, Kai Kang e Jing Wu. "Multipath Cross Graph Convolution for Knowledge Representation Learning". Computational Intelligence and Neuroscience 2021 (28 de dezembro de 2021): 1–13. http://dx.doi.org/10.1155/2021/2547905.
Texto completo da fonteLiu, Q., e Y. Dong. "DEEP FEATURE EXTRACTION BASED ON DYNAMIC GRAPH CONVOLUTIONAL NETWORKS FOR ACCELERATED HYPERSPECTRAL IMAGE CLASSIFICATION". ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2022 (17 de maio de 2022): 139–46. http://dx.doi.org/10.5194/isprs-annals-v-3-2022-139-2022.
Texto completo da fonteHao, Jiao, Zongbao Zhang e Yihan Ping. "Power System Fault Diagnosis and Prediction System Based on Graph Neural Network". International Journal of Information Technologies and Systems Approach 17, n.º 1 (17 de janeiro de 2024): 1–14. http://dx.doi.org/10.4018/ijitsa.336475.
Texto completo da fonteBhatti, Uzair Aslam, Hao Tang, Guilu Wu, Shah Marjan e Aamir Hussain. "Deep Learning with Graph Convolutional Networks: An Overview and Latest Applications in Computational Intelligence". International Journal of Intelligent Systems 2023 (28 de fevereiro de 2023): 1–28. http://dx.doi.org/10.1155/2023/8342104.
Texto completo da fonteSun, Linhui, Yifan Zhang, Jian Cheng e Hanqing Lu. "Asynchronous Event Processing with Local-Shift Graph Convolutional Network". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 2 (26 de junho de 2023): 2402–10. http://dx.doi.org/10.1609/aaai.v37i2.25336.
Texto completo da fonteWang, Yucheng, Yuecong Xu, Jianfei Yang, Min Wu, Xiaoli Li, Lihua Xie e Zhenghua Chen. "Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 14 (24 de março de 2024): 15715–24. http://dx.doi.org/10.1609/aaai.v38i14.29500.
Texto completo da fonteLi, Liangwei, Lin Liu, Xiaohui Du, Xiangzhou Wang, Ziruo Zhang, Jing Zhang, Ping Zhang e Juanxiu Liu. "CGUN-2A: Deep Graph Convolutional Network via Contrastive Learning for Large-Scale Zero-Shot Image Classification". Sensors 22, n.º 24 (18 de dezembro de 2022): 9980. http://dx.doi.org/10.3390/s22249980.
Texto completo da fonteHu, Ruiqi, Shirui Pan, Guodong Long, Qinghua Lu, Liming Zhu e Jing Jiang. "Going Deep: Graph Convolutional Ladder-Shape Networks". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 03 (3 de abril de 2020): 2838–45. http://dx.doi.org/10.1609/aaai.v34i03.5673.
Texto completo da fonteWang, Yu, Liang Hu, Yang Wu e Wanfu Gao. "Graph Multihead Attention Pooling with Self-Supervised Learning". Entropy 24, n.º 12 (29 de novembro de 2022): 1745. http://dx.doi.org/10.3390/e24121745.
Texto completo da fonteHan, Xiao, Jing Peng, Tailai Peng, Rui Chen, Boyuan Hou, Xinran Xie e Zhe Cui. "The Status and Trend of Chinese News Forecast Based on Graph Convolutional Network Pooling Algorithm". Applied Sciences 12, n.º 2 (17 de janeiro de 2022): 900. http://dx.doi.org/10.3390/app12020900.
Texto completo da fontePham, Hai Van, Dat Hoang Thanh e Philip Moore. "Hierarchical Pooling in Graph Neural Networks to Enhance Classification Performance in Large Datasets". Sensors 21, n.º 18 (10 de setembro de 2021): 6070. http://dx.doi.org/10.3390/s21186070.
Texto completo da fonteDuan, Yutai, Jianming Wang, Haoran Ma e Yukuan Sun. "Residual convolutional graph neural network with subgraph attention pooling". Tsinghua Science and Technology 27, n.º 4 (agosto de 2022): 653–63. http://dx.doi.org/10.26599/tst.2021.9010058.
Texto completo da fonteZhang, Shuoyan, Jiacheng Yang, Ying Zhang, Jiayi Zhong, Wenjing Hu, Chenyang Li e Jiehui Jiang. "The Combination of a Graph Neural Network Technique and Brain Imaging to Diagnose Neurological Disorders: A Review and Outlook". Brain Sciences 13, n.º 10 (16 de outubro de 2023): 1462. http://dx.doi.org/10.3390/brainsci13101462.
Texto completo da fonteYang, Yukun, Bo Ma, Xiangdong Liu, Liang Zhao e Shoudong Huang. "GSAP: A Global Structure Attention Pooling Method for Graph-Based Visual Place Recognition". Remote Sensing 13, n.º 8 (10 de abril de 2021): 1467. http://dx.doi.org/10.3390/rs13081467.
Texto completo da fonteMa, Tianle, e Aidong Zhang. "AffinityNet: Semi-Supervised Few-Shot Learning for Disease Type Prediction". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julho de 2019): 1069–76. http://dx.doi.org/10.1609/aaai.v33i01.33011069.
Texto completo da fonteHou, Wentai, Lequan Yu, Chengxuan Lin, Helong Huang, Rongshan Yu, Jing Qin e Liansheng Wang. "H^2-MIL: Exploring Hierarchical Representation with Heterogeneous Multiple Instance Learning for Whole Slide Image Analysis". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 1 (28 de junho de 2022): 933–41. http://dx.doi.org/10.1609/aaai.v36i1.19976.
Texto completo da fonteYan, Jiayi, Shaohui Wang, Jing Lin, Peihao Li, Ruxin Zhang e Haoqian Wang. "GaitSG: Gait Recognition with SMPLs in Graph Structure". Sensors 23, n.º 20 (22 de outubro de 2023): 8627. http://dx.doi.org/10.3390/s23208627.
Texto completo da fonteYan, Xiongfeng, e Min Yang. "A Comparative Study of Various Deep Learning Approaches to Shape Encoding of Planar Geospatial Objects". ISPRS International Journal of Geo-Information 11, n.º 10 (18 de outubro de 2022): 527. http://dx.doi.org/10.3390/ijgi11100527.
Texto completo da fonteShao, Dangguo, Zihan He, Hongbo Fan e Kun Sun. "Detection of Cattle Key Parts Based on the Improved Yolov5 Algorithm". Agriculture 13, n.º 6 (23 de maio de 2023): 1110. http://dx.doi.org/10.3390/agriculture13061110.
Texto completo da fonteHu, Kai, Jiasheng Wu, Yaogen Li, Meixia Lu, Liguo Weng e Min Xia. "FedGCN: Federated Learning-Based Graph Convolutional Networks for Non-Euclidean Spatial Data". Mathematics 10, n.º 6 (21 de março de 2022): 1000. http://dx.doi.org/10.3390/math10061000.
Texto completo da fonteEmbarcadero-Ruiz, Daniel, Helena Gómez-Adorno, Alberto Embarcadero-Ruiz e Gerardo Sierra. "Graph-Based Siamese Network for Authorship Verification". Mathematics 10, n.º 2 (17 de janeiro de 2022): 277. http://dx.doi.org/10.3390/math10020277.
Texto completo da fonteLu, Zhengqiu, Chunliang Zhou, Xuyang Xuyang e Weipeng Zhang. "Face Detection and Recognition Method Based on Improved Convolutional Neural Network". International Journal of Circuits, Systems and Signal Processing 15 (30 de julho de 2021): 774–81. http://dx.doi.org/10.46300/9106.2021.15.85.
Texto completo da fonteZhao, Hongyu, Jiazhi Xie e Hongbin Wang. "Graph Convolutional Network Based on Multi-Head Pooling for Short Text Classification". IEEE Access 10 (2022): 11947–56. http://dx.doi.org/10.1109/access.2022.3146303.
Texto completo da fonteDu, Yinan, Jian Tang, Ting Rui, Xinxin Li e Chengsong Yang. "GBP: Graph convolutional network embedded in bilinear pooling for fine-grained encoding". Computers and Electrical Engineering 116 (maio de 2024): 109158. http://dx.doi.org/10.1016/j.compeleceng.2024.109158.
Texto completo da fontePang, Bo, Zhongtian Zheng, Guoping Wang e Peng-Shuai Wang. "Learning the Geodesic Embedding with Graph Neural Networks". ACM Transactions on Graphics 42, n.º 6 (5 de dezembro de 2023): 1–12. http://dx.doi.org/10.1145/3618317.
Texto completo da fonteLei, Fangyuan, Xun Liu, Qingyun Dai, Bingo Wing-Kuen Ling, Huimin Zhao e Yan Liu. "Hybrid Low-Order and Higher-Order Graph Convolutional Networks". Computational Intelligence and Neuroscience 2020 (23 de junho de 2020): 1–9. http://dx.doi.org/10.1155/2020/3283890.
Texto completo da fonteHuang, Linjiang, Yan Huang, Wanli Ouyang e Liang Wang. "Part-Level Graph Convolutional Network for Skeleton-Based Action Recognition". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 07 (3 de abril de 2020): 11045–52. http://dx.doi.org/10.1609/aaai.v34i07.6759.
Texto completo da fonteYang, Rong, Junyu Niu, Ying Xu, Yun Wang e Li Qiu. "Action Recognition Based on GCN with Adjacency Matrix Generation Module and Time Domain Attention Mechanism". Symmetry 15, n.º 10 (23 de outubro de 2023): 1954. http://dx.doi.org/10.3390/sym15101954.
Texto completo da fonteChen, Yuxin, Gaoqun Ma, Chunfeng Yuan, Bing Li, Hui Zhang, Fangshi Wang e Weiming Hu. "Graph convolutional network with structure pooling and joint-wise channel attention for action recognition". Pattern Recognition 103 (julho de 2020): 107321. http://dx.doi.org/10.1016/j.patcog.2020.107321.
Texto completo da fonteAndriyanov, Nikita. "Application of Graph Structures in Computer Vision Tasks". Mathematics 10, n.º 21 (29 de outubro de 2022): 4021. http://dx.doi.org/10.3390/math10214021.
Texto completo da fonteJi, Xiujuan, Lei Liu e Jingwen Zhu. "Code Clone Detection with Hierarchical Attentive Graph Embedding". International Journal of Software Engineering and Knowledge Engineering 31, n.º 06 (junho de 2021): 837–61. http://dx.doi.org/10.1142/s021819402150025x.
Texto completo da fonteHan, Xianquan, Xijiang Chen, Hui Deng, Peng Wan e Jianzhou Li. "Point Cloud Deep Learning Network Based on Local Domain Multi-Level Feature". Applied Sciences 13, n.º 19 (28 de setembro de 2023): 10804. http://dx.doi.org/10.3390/app131910804.
Texto completo da fonteLiu, Xun, Guoqing Xia, Fangyuan Lei, Yikuan Zhang e Shihui Chang. "Higher-Order Graph Convolutional Networks With Multi-Scale Neighborhood Pooling for Semi-Supervised Node Classification". IEEE Access 9 (2021): 31268–75. http://dx.doi.org/10.1109/access.2021.3060173.
Texto completo da fontePal, Monalin, e Rubini P. "Fusion of Brain Imaging Data with Artificial Intelligence to detect Autism Spectrum Disorder". Fusion: Practice and Applications 14, n.º 2 (2024): 89–96. http://dx.doi.org/10.54216/fpa.140207.
Texto completo da fonteRodziewicz-Bielewicz, Jan, e Marcin Korzeń. "Comparison of Graph Fitting and Sparse Deep Learning Model for Robot Pose Estimation". Sensors 22, n.º 17 (29 de agosto de 2022): 6518. http://dx.doi.org/10.3390/s22176518.
Texto completo da fonteYang, Boming. "Image processing based on neural networks". Applied and Computational Engineering 10, n.º 1 (25 de setembro de 2023): 272–81. http://dx.doi.org/10.54254/2755-2721/10/20230193.
Texto completo da fonteLuo, Wanli, e Jialiang Wang. "The Application of A-CNN in Crowd Counting of Scenic Spots". Journal of Advanced Computational Intelligence and Intelligent Informatics 23, n.º 2 (20 de março de 2019): 305–8. http://dx.doi.org/10.20965/jaciii.2019.p0305.
Texto completo da fonteGu, Jindong. "Interpretable Graph Capsule Networks for Object Recognition". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 2 (18 de maio de 2021): 1469–77. http://dx.doi.org/10.1609/aaai.v35i2.16237.
Texto completo da fonteLiu, Chao, Buhong Wang, Zhen Wang, Jiwei Tian, Peng Luo e Yong Yang. "TCFLTformer: TextCNN-Flat-Lattice Transformer for Entity Recognition of Air Traffic Management Cyber Threat Knowledge Graphs". Aerospace 10, n.º 8 (7 de agosto de 2023): 697. http://dx.doi.org/10.3390/aerospace10080697.
Texto completo da fonteYu, Bing, Yan Huang, Guang Cheng, Dongjin Huang e Youdong Ding. "Graph U-Shaped Network with Mapping-Aware Local Enhancement for Single-Frame 3D Human Pose Estimation". Electronics 12, n.º 19 (2 de outubro de 2023): 4120. http://dx.doi.org/10.3390/electronics12194120.
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