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Yunshan Cup 2020: Overview of the Part-of-Speech Tagging Task for Low-resourced Languages., , , , , и . CoRR, (2022)Effective Graph Kernels for Evolving Functional Brain Networks., , , , , и . WSDM, стр. 150-158. ACM, (2023)Transformer with Spatio-Temporal Representation for Video Anomaly Detection., , , и . S+SSPR, том 13813 из Lecture Notes in Computer Science, стр. 213-222. Springer, (2022)HAEP: Heterogeneous Environment Aware Edge Partitioning for Power-Law Graphs., , , , и . DASFAA (3), том 13945 из Lecture Notes in Computer Science, стр. 331-340. Springer, (2023)An effective variational auto-encoder-based model for traffic flow imputation., , , , и . Neural Comput. Appl., 36 (5): 2617-2631 (февраля 2024)Effective and efficient community search with size constraint on bipartite graphs., , , , , и . Inf. Sci., (ноября 2023)CCFD-GAN: Credit Card Fraud Detection Based on Generative Adversarial Networks Enhanced by Penalty Mechanism., , , и . IJCNN, стр. 1-8. IEEE, (2023)Multi-memory video anomaly detection based on scene object distribution., , , , и . Multim. Tools Appl., 82 (23): 35557-35583 (сентября 2023)MPAT: multi-path attention temporal method for video anomaly detection., , , , , , и . Multim. Tools Appl., 82 (8): 12557-12575 (марта 2023)FOAD: a novel video anomaly detection focusing on objects., , , , , и . Multim. Tools Appl., 83 (7): 20637-20651 (2024)