Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Junpeng Bao"'
Publikováno v:
PLoS ONE, Vol 13, Iss 4, p e0196108 (2018)
Many important applications continuously generate data, such as financial transaction administration, satellite monitoring, network flow monitoring, and web information processing. The data mining results are always evolving with the newly generated
Externí odkaz:
https://doaj.org/article/07fb922df64648f8943b7f1de4428d13
Publikováno v:
Information Sciences. 589:813-826
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::414551007b2f0316baea571aef29b26f
https://doi.org/10.1016/j.ins.2021.12.037
https://doi.org/10.1016/j.ins.2021.12.037
Publikováno v:
IFIP Advances in Information and Communication Technology ISBN: 9783031341069
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c425ad6e78e82ce44491beb99a16cc10
https://doi.org/10.1007/978-3-031-34107-6_19
https://doi.org/10.1007/978-3-031-34107-6_19
Publikováno v:
Journal of Intelligent Manufacturing. 32:1711-1727
Time series data is pervasive in many applications and the anomaly detection about it is important, which will provide the early warning of some unexpected patterns. In this paper, we propose a multiple similarity based anomalous subsequences detecti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eb1520f63100077697dd7433d89714dd
https://doi.org/10.1007/s10845-020-01583-0
https://doi.org/10.1007/s10845-020-01583-0
Publikováno v:
Archives of Virology. 164:2119-2129
Rabies is a fatal disease caused by infection with rabies virus (RABV), and human rabies is still a critical public-health concern in China. Although there have been some phylogenetic studies about RABV transmission patterns, with the accumulation of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::506c0de1afb018b72a7532b356d64a8b
https://doi.org/10.1007/s00705-019-04297-8
https://doi.org/10.1007/s00705-019-04297-8
Publikováno v:
2020 2nd International Conference on Image Processing and Machine Vision.
Knowledge graph-based dialogue systems can narrow down knowledge candidates for generating informative and diverse responses with the use of prior information, e.g., triple attributes or graph paths. However, most current knowledge graph (KG) cover i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e0697a45112dc741734e549e5e468532
https://doi.org/10.1145/3421558.3421564
https://doi.org/10.1145/3421558.3421564
Publikováno v:
Proceedings of the 2020 10th International Conference on Bioscience, Biochemistry and Bioinformatics.
Seasonal pandemics of influenza A viruses bring enormous threaten to human healthy. Different subtypes of influenza A viruses disseminated in human have variable susceptibilities to antiviral drug, so rapid subtyping of influenza A viruses has been i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d734b7e878a53a90479d75cf6ade899d
https://doi.org/10.1145/3386052.3386053
https://doi.org/10.1145/3386052.3386053
Autor:
Junpeng Bao, Xinyi Li
Publikováno v:
2019 2nd International Conference on Safety Produce Informatization (IICSPI).
Exploration on the time series data in unknown model pattern recognition has important research significance. This paper proposes an unknown pattern detection method for time-series data based on convolution neural network, which planifies the output
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eee38736d7a9195f81992a118b664405
https://doi.org/10.1109/iicspi48186.2019.9095913
https://doi.org/10.1109/iicspi48186.2019.9095913
Background: Protein remote homology detection has long received great attention in the field of bioinformatics, but the property of low protein sequence similarities heavily influences the accuracy of detection. Recently, such deep learning methods a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::01233613b8f73d45380fbed0642636ac
https://doi.org/10.21203/rs.2.15388/v1
https://doi.org/10.21203/rs.2.15388/v1
Publikováno v:
Communications in Computer and Information Science ISBN: 9789811359095
Many time series anomaly detection algorithms are hard to be applied in real scenarios for two reasons. Firstly some of them are supervised since training data is required to define the normal behavior, but it is expensive to annotate the normal part
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::64f4e659875e38797f45d19b6d2c6c41
https://doi.org/10.1007/978-981-13-5910-1_8
https://doi.org/10.1007/978-981-13-5910-1_8