Artículos de revistas sobre el tema "Temporal Graph Processing"
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Christensen, Andrew J., Ananya Sen Gupta y Ivars Kirsteins. "Sonar target feature representation using temporal graph networks". Journal of the Acoustical Society of America 151, n.º 4 (abril de 2022): A102. http://dx.doi.org/10.1121/10.0010791.
Texto completoChoi, Jeongwhan, Hwangyong Choi, Jeehyun Hwang y Noseong Park. "Graph Neural Controlled Differential Equations for Traffic Forecasting". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 6 (28 de junio de 2022): 6367–74. http://dx.doi.org/10.1609/aaai.v36i6.20587.
Texto completoZhao, Xiaojuan, Aiping Li, Rong Jiang, Kai Chen y Zhichao Peng. "Householder Transformation-Based Temporal Knowledge Graph Reasoning". Electronics 12, n.º 9 (26 de abril de 2023): 2001. http://dx.doi.org/10.3390/electronics12092001.
Texto completoLiu, Jun. "Motion Action Analysis at Basketball Sports Scene Based on Image Processing". Scientific Programming 2022 (7 de marzo de 2022): 1–11. http://dx.doi.org/10.1155/2022/7349548.
Texto completoLi, Jing, Wenyue Guo, Haiyan Liu, Xin Chen, Anzhu Yu y Jia Li. "Predicting User Activity Intensity Using Geographic Interactions Based on Social Media Check-In Data". ISPRS International Journal of Geo-Information 10, n.º 8 (17 de agosto de 2021): 555. http://dx.doi.org/10.3390/ijgi10080555.
Texto completoKe, Xiangyu, Arijit Khan y Francesco Bonchi. "Multi-relation Graph Summarization". ACM Transactions on Knowledge Discovery from Data 16, n.º 5 (31 de octubre de 2022): 1–30. http://dx.doi.org/10.1145/3494561.
Texto completoZhang, Guoxing, Haixiao Wang y Yuanpu Yin. "Multi-type Parameter Prediction of Traffic Flow Based on Time-space Attention Graph Convolutional Network". International Journal of Circuits, Systems and Signal Processing 15 (11 de agosto de 2021): 902–12. http://dx.doi.org/10.46300/9106.2021.15.97.
Texto completoZheng, Xiaolong, Dongdong Guan, Bangjie Li, Zhengsheng Chen y Lefei Pan. "Global and Local Graph-Based Difference Image Enhancement for Change Detection". Remote Sensing 15, n.º 5 (21 de febrero de 2023): 1194. http://dx.doi.org/10.3390/rs15051194.
Texto completoSteinbauer, Matthias y Gabriele Anderst Kotsis. "DynamoGraph: extending the Pregel paradigm for large-scale temporal graph processing". International Journal of Grid and Utility Computing 7, n.º 2 (2016): 141. http://dx.doi.org/10.1504/ijguc.2016.077491.
Texto completoChen, Yaosen, Bing Guo, Yan Shen, Wei Wang, Weichen Lu y Xinhua Suo. "Boundary graph convolutional network for temporal action detection". Image and Vision Computing 109 (mayo de 2021): 104144. http://dx.doi.org/10.1016/j.imavis.2021.104144.
Texto completoSun, Linhui, Yifan Zhang, Jian Cheng y 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 junio de 2023): 2402–10. http://dx.doi.org/10.1609/aaai.v37i2.25336.
Texto completoZeng, Hui, Chaojie Jiang, Yuanchun Lan, Xiaohui Huang, Junyang Wang y Xinhua Yuan. "Long Short-Term Fusion Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting". Electronics 12, n.º 1 (3 de enero de 2023): 238. http://dx.doi.org/10.3390/electronics12010238.
Texto completoGLAVAŠ, GORAN y JAN ŠNAJDER. "Construction and evaluation of event graphs". Natural Language Engineering 21, n.º 4 (1 de mayo de 2014): 607–52. http://dx.doi.org/10.1017/s1351324914000060.
Texto completoFang, Junhua, Jiafeng Ding, Pengpeng Zhao, Jiajie Xu, An Liu y Zhixu Li. "Distributed and parallel processing for real-time and dynamic spatio-temporal graph". World Wide Web 23, n.º 2 (18 de noviembre de 2019): 905–26. http://dx.doi.org/10.1007/s11280-019-00741-6.
Texto completoKörner, Christof, Margit Höfler, Barbara Tröbinger y Iain D. Gilchrist. "Eye Movements Indicate the Temporal Organisation of Information Processing in Graph Comprehension". Applied Cognitive Psychology 28, n.º 3 (12 de febrero de 2014): 360–73. http://dx.doi.org/10.1002/acp.3006.
Texto completoWang, Xiaojuan, Ziliang Gan, Lei Jin, Yabo Xiao y Mingshu He. "Adaptive Multi-Scale Difference Graph Convolution Network for Skeleton-Based Action Recognition". Electronics 12, n.º 13 (28 de junio de 2023): 2852. http://dx.doi.org/10.3390/electronics12132852.
Texto completoKerracher, Natalie, Jessie Kennedy y Kevin Chalmers. "A Task Taxonomy for Temporal Graph Visualisation". IEEE Transactions on Visualization and Computer Graphics 21, n.º 10 (1 de octubre de 2015): 1160–72. http://dx.doi.org/10.1109/tvcg.2015.2424889.
Texto completoEl rai, Marwa Chendeb, Muna Darweesh y Mina Al-Saad. "Semi-Supervised Segmentation of Echocardiography Videos Using Graph Signal Processing". Electronics 11, n.º 21 (26 de octubre de 2022): 3462. http://dx.doi.org/10.3390/electronics11213462.
Texto completoXue, Jizhong, Zaohui Kang, Chun Sing Lai, Yu Wang, Fangyuan Xu y Haoliang Yuan. "Distributed Generation Forecasting Based on Rolling Graph Neural Network (ROLL-GNN)". Energies 16, n.º 11 (31 de mayo de 2023): 4436. http://dx.doi.org/10.3390/en16114436.
Texto completoLiu, Zhi, Jixin Bian, Deju Zhang, Yang Chen, Guojiang Shen y Xiangjie Kong. "Dynamic Multi-View Coupled Graph Convolution Network for Urban Travel Demand Forecasting". Electronics 11, n.º 16 (21 de agosto de 2022): 2620. http://dx.doi.org/10.3390/electronics11162620.
Texto completoLi, Tingwei, Ruiwen Zhang y Qing Li. "A Novel Graph Representation for Skeleton-based Action Recognition". Signal & Image Processing : An International Journal 11, n.º 6 (30 de diciembre de 2020): 65–73. http://dx.doi.org/10.5121/sipij.2020.11605.
Texto completoLi, Chaoyue, Lian Zou, Cien Fan, Hao Jiang y Yifeng Liu. "Multi-Stage Attention-Enhanced Sparse Graph Convolutional Network for Skeleton-Based Action Recognition". Electronics 10, n.º 18 (8 de septiembre de 2021): 2198. http://dx.doi.org/10.3390/electronics10182198.
Texto completoBinsfeld Gonçalves, Laurent, Ivan Nesic, Marko Obradovic, Bram Stieltjes, Thomas Weikert y Jens Bremerich. "Natural Language Processing and Graph Theory: Making Sense of Imaging Records in a Novel Representation Frame". JMIR Medical Informatics 10, n.º 12 (21 de diciembre de 2022): e40534. http://dx.doi.org/10.2196/40534.
Texto completoTomei, Matteo, Lorenzo Baraldi, Simone Calderara, Simone Bronzin y Rita Cucchiara. "Video action detection by learning graph-based spatio-temporal interactions". Computer Vision and Image Understanding 206 (mayo de 2021): 103187. http://dx.doi.org/10.1016/j.cviu.2021.103187.
Texto completoWang, Daocheng, Chao Chen, Chong Di y Minglei Shu. "Exploring Behavior Patterns for Next-POI Recommendation via Graph Self-Supervised Learning". Electronics 12, n.º 8 (20 de abril de 2023): 1939. http://dx.doi.org/10.3390/electronics12081939.
Texto completoLi, Huiyong, Xiaofeng Wu y Yanhong Wang. "Dynamic Performance Analysis of STEP System in Internet of Vehicles Based on Queuing Theory". Computational Intelligence and Neuroscience 2022 (10 de abril de 2022): 1–13. http://dx.doi.org/10.1155/2022/8322029.
Texto completoKaruza, Elisabeth A., Ari E. Kahn y Danielle S. Bassett. "Human Sensitivity to Community Structure Is Robust to Topological Variation". Complexity 2019 (11 de febrero de 2019): 1–8. http://dx.doi.org/10.1155/2019/8379321.
Texto completoBayram, Ulya, Runia Roy, Aqil Assalil y Lamia BenHiba. "The unknown knowns: a graph-based approach for temporal COVID-19 literature mining". Online Information Review 45, n.º 4 (23 de marzo de 2021): 687–708. http://dx.doi.org/10.1108/oir-12-2020-0562.
Texto completoCarrillo, Rafael E., Martin Leblanc, Baptiste Schubnel, Renaud Langou, Cyril Topfel y Pierre-Jean Alet. "High-Resolution PV Forecasting from Imperfect Data: A Graph-Based Solution". Energies 13, n.º 21 (3 de noviembre de 2020): 5763. http://dx.doi.org/10.3390/en13215763.
Texto completoAqil, Marco, Selen Atasoy, Morten L. Kringelbach y Rikkert Hindriks. "Graph neural fields: A framework for spatiotemporal dynamical models on the human connectome". PLOS Computational Biology 17, n.º 1 (28 de enero de 2021): e1008310. http://dx.doi.org/10.1371/journal.pcbi.1008310.
Texto completoGuda, Vanitha y SureshKumar Sanampudi. "Event Time Relationship in Natural Language Text". International Journal of Recent Contributions from Engineering, Science & IT (iJES) 7, n.º 3 (25 de septiembre de 2019): 4. http://dx.doi.org/10.3991/ijes.v7i3.10985.
Texto completoHuang, Xiaohui, Yuanchun Lan, Yuming Ye, Junyang Wang y Yuan Jiang. "Traffic Flow Prediction Based on Multi-Mode Spatial-Temporal Convolution of Mixed Hop Diffuse ODE". Electronics 11, n.º 19 (22 de septiembre de 2022): 3012. http://dx.doi.org/10.3390/electronics11193012.
Texto completoGhosh, Dipon Kumar, Amitabha Chakrabarty, Hyeonjoon Moon y M. Jalil Piran. "A Spatio-Temporal Graph Convolutional Network Model for Internet of Medical Things (IoMT)". Sensors 22, n.º 21 (2 de noviembre de 2022): 8438. http://dx.doi.org/10.3390/s22218438.
Texto completoHe, Jiatong, Jia Cui, Gaobo Zhang, Mingrui Xue, Dengyu Chu y Yanna Zhao. "Spatial–temporal seizure detection with graph attention network and bi-directional LSTM architecture". Biomedical Signal Processing and Control 78 (septiembre de 2022): 103908. http://dx.doi.org/10.1016/j.bspc.2022.103908.
Texto completoZhao, Mengyao, Zhengping Hu, Shufang Li, Shuai Bi y Zhe Sun. "Two-stream graph convolutional neural network fusion for weakly supervised temporal action detection". Signal, Image and Video Processing 16, n.º 4 (11 de octubre de 2021): 947–54. http://dx.doi.org/10.1007/s11760-021-02039-5.
Texto completoShuai, Wenjing, Fenlong Jiang, Hanhong Zheng y Jianzhao Li. "MSGATN: A Superpixel-Based Multi-Scale Siamese Graph Attention Network for Change Detection in Remote Sensing Images". Applied Sciences 12, n.º 10 (20 de mayo de 2022): 5158. http://dx.doi.org/10.3390/app12105158.
Texto completoWu, Lei, Yong Tang, Pei Zhang y Ying Zhou. "Spatio-Temporal Heterogeneous Graph Neural Networks for Estimating Time of Travel". Electronics 12, n.º 6 (8 de marzo de 2023): 1293. http://dx.doi.org/10.3390/electronics12061293.
Texto completoCao, Yibo, Lu Liu y Yuhan Dong. "Convolutional Long Short-Term Memory Two-Dimensional Bidirectional Graph Convolutional Network for Taxi Demand Prediction". Sustainability 15, n.º 10 (11 de mayo de 2023): 7903. http://dx.doi.org/10.3390/su15107903.
Texto completoHuang, Wanrong, Xiaodong Yi, Yichun Sun, Yingwen Liu, Shuai Ye y Hengzhu Liu. "Scalable Parallel Distributed Coprocessor System for Graph Searching Problems with Massive Data". Scientific Programming 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/1496104.
Texto completoRozhdestvenskaya, К. N. "Temporal analysis of a control system in a data processing network". Information and Control Systems, n.º 1 (19 de febrero de 2019): 32–39. http://dx.doi.org/10.31799/1684-8853-2019-1-32-39.
Texto completoPang, Shiyan, Xiangyun Hu, Mi Zhang, Zhongliang Cai y Fengzhu Liu. "Co-Segmentation and Superpixel-Based Graph Cuts for Building Change Detection from Bi-Temporal Digital Surface Models and Aerial Images". Remote Sensing 11, n.º 6 (26 de marzo de 2019): 729. http://dx.doi.org/10.3390/rs11060729.
Texto completoDo, M. y S. Kambhampati. "SAPA: A Multi-objective Metric Temporal Planner". Journal of Artificial Intelligence Research 20 (1 de diciembre de 2003): 155–94. http://dx.doi.org/10.1613/jair.1156.
Texto completoSighencea, Bogdan Ilie, Ion Rareș Stanciu y Cătălin Daniel Căleanu. "D-STGCN: Dynamic Pedestrian Trajectory Prediction Using Spatio-Temporal Graph Convolutional Networks". Electronics 12, n.º 3 (26 de enero de 2023): 611. http://dx.doi.org/10.3390/electronics12030611.
Texto completoWeghenkel, Björn y Laurenz Wiskott. "Slowness as a Proxy for Temporal Predictability: An Empirical Comparison". Neural Computation 30, n.º 5 (mayo de 2018): 1151–79. http://dx.doi.org/10.1162/neco_a_01070.
Texto completoShi, Yong, Yang Xiao, Pei Quan, MingLong Lei y Lingfeng Niu. "Document-level relation extraction via graph transformer networks and temporal convolutional networks". Pattern Recognition Letters 149 (septiembre de 2021): 150–56. http://dx.doi.org/10.1016/j.patrec.2021.06.012.
Texto completoPan, Chengsheng, Jiang Zhu, Zhixiang Kong, Huaifeng Shi y Wensheng Yang. "DC-STGCN: Dual-Channel Based Graph Convolutional Networks for Network Traffic Forecasting". Electronics 10, n.º 9 (24 de abril de 2021): 1014. http://dx.doi.org/10.3390/electronics10091014.
Texto completoFeng, Yongliang. "Air Quality Prediction Model Using Deep Learning in Internet of Things Environmental Monitoring System". Mobile Information Systems 2022 (29 de septiembre de 2022): 1–9. http://dx.doi.org/10.1155/2022/7221157.
Texto completoHu, Zhiqiu, Fengjing Shao y Rencheng Sun. "A New Perspective on Traffic Flow Prediction: A Graph Spatial-Temporal Network with Complex Network Information". Electronics 11, n.º 15 (4 de agosto de 2022): 2432. http://dx.doi.org/10.3390/electronics11152432.
Texto completoZhu, Qilin, Hongmin Deng y Kaixuan Wang. "Skeleton Action Recognition Based on Temporal Gated Unit and Adaptive Graph Convolution". Electronics 11, n.º 18 (19 de septiembre de 2022): 2973. http://dx.doi.org/10.3390/electronics11182973.
Texto completoZhong, Yang Jun y Qian Cai. "A Novel Registration Approach for Mammograms Based on SIFT and Graph Transformation". Applied Mechanics and Materials 157-158 (febrero de 2012): 1313–19. http://dx.doi.org/10.4028/www.scientific.net/amm.157-158.1313.
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