Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Kaiqun Fu"'
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 8, Pp 4729-4742 (2022)
Anomaly detection over traffic data is crucial for transportation management and abnormal behavior identification. An anomaly in real-world scenarios usually causes abnormal observations for multiple detectors in an extended period. However, existing
Externí odkaz:
https://doaj.org/article/82fd8813076d4bf3ad11dc4f22bf052c
Publikováno v:
2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ecef10352e486d86c73da07c8504b5d
https://doi.org/10.1109/itsc55140.2022.9922211
https://doi.org/10.1109/itsc55140.2022.9922211
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031159305
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::50fc57a423a56b7ae0250ecbee994f51
https://doi.org/10.1007/978-3-031-15931-2_50
https://doi.org/10.1007/978-3-031-15931-2_50
Autor:
Omer Zulfiqar, Yi-Chun Chang, Po-Han Chen, Kaiqun Fu, Chang-Tien Lu, David Solnick, Yanlin Li
Publikováno v:
Lecture Notes in Social Networks ISBN: 9783031082412
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::110e8580cd9f419d1d3bf284bd9c1062
https://doi.org/10.1007/978-3-031-08242-9_5
https://doi.org/10.1007/978-3-031-08242-9_5
Publikováno v:
2021 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::48eb6ccb88715950d096a1e237924e73
https://doi.org/10.1109/bigdata52589.2021.9672030
https://doi.org/10.1109/bigdata52589.2021.9672030
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:13075-13076
Chinese characters have semantic-rich compositional information in radical form. While almost all previous research has applied CNNs to extract this compositional information, our work utilizes deep graph learning on a compact, graph-based representa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::37b2dd99177ecd6a9e8bee2c99c3c087
https://doi.org/10.1609/aaai.v36i11.21674
https://doi.org/10.1609/aaai.v36i11.21674
Autor:
Zonghan Zhang, Subhodip Biswas, Fanglan Chen, Kaiqun Fu, Taoran Ji, Chang-Tien Lu, Naren Ramakrishnan, Zhiqian Chen
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:13115-13116
Influence blocking maximization (IBM) is crucial in many critical real-world problems such as rumors prevention and epidemic containment. The existing work suffers from: (1) concentrating on uniform costs at the individual level, (2) mostly utilizing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::99227c6ca895869cee9137b7ee4f12d1
https://doi.org/10.1609/aaai.v36i11.21694
https://doi.org/10.1609/aaai.v36i11.21694
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:13015-13016
Predicting and quantifying the impact of traffic accidents is necessary and critical to Intelligent Transport Systems (ITS). As a state-of-the-art technique in graph learning, current graph neural networks heavily rely on graph Fourier transform, ass
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f7ac322358323346c61802a82bad8a17
https://doi.org/10.1609/aaai.v36i11.21644
https://doi.org/10.1609/aaai.v36i11.21644
Publikováno v:
SIGSPATIAL Special. 11:16-25
The exponential growth of the urban data generated by urban sensors, government reports, and crowd-sourcing services endorses the rapid development of urban computing and spatial data mining technologies. Easier accessibility to such enormous urban d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ced6ff961189985e827ac2693fd96d43
https://doi.org/10.1145/3377000.3377003
https://doi.org/10.1145/3377000.3377003
Publikováno v:
IEEE BigData
Amidst the COVID-19 pandemic, cyberbullying has become an even more serious threat. Our work aims to investigate the viability of an automatic multiclass cyberbullying detection model that is able to classify whether a cyberbully is targeting a victi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::13d59454ad21c768d99f83a5cfa7a5a4
https://doi.org/10.1109/bigdata50022.2020.9378065
https://doi.org/10.1109/bigdata50022.2020.9378065