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pro vyhledávání: '"Wu, Peilun"'
In order to meet the demand for higher scene rendering quality from some autonomous driving teams (such as those focused on CV), we have decided to use an offline simulation industrial rendering framework instead of real-time rendering in our autonom
Externí odkaz:
http://arxiv.org/abs/2306.15176
Autor:
Wu, Peilun, Guo, Hui
Email threat is a serious issue for enterprise security. The threat can be in various malicious forms, such as phishing, fraud, blackmail and malvertisement. The traditional anti-spam gateway often maintains a greylist to filter out unexpected emails
Externí odkaz:
http://arxiv.org/abs/2104.08044
Network intrusion detection (NID) is an essential defense strategy that is used to discover the trace of suspicious user behaviour in large-scale cyberspace, and machine learning (ML), due to its capability of automation and intelligence, has been gr
Externí odkaz:
http://arxiv.org/abs/2010.12171
High false alarm rate and low detection rate are the major sticking points for unknown threat perception. To address the problems, in the paper, we present a densely connected residual network (Densely-ResNet) for attack recognition. Densely-ResNet i
Externí odkaz:
http://arxiv.org/abs/2008.02196
One challenge for building a secure network communication environment is how to effectively detect and prevent malicious network behaviours. The abnormal network activities threaten users' privacy and potentially damage the function and infrastructur
Externí odkaz:
http://arxiv.org/abs/2001.08523
Autor:
Wu, Peilun, Guo, Hui
Network attack is a significant security issue for modern society. From small mobile devices to large cloud platforms, almost all computing products, used in our daily life, are networked and potentially under the threat of network intrusion. With th
Externí odkaz:
http://arxiv.org/abs/1909.10031
Convolution Neural Network (ConvNet) offers a high potential to generalize input data. It has been widely used in many application areas, such as visual imagery, where comprehensive learning datasets are available and a ConvNet model can be well trai
Externí odkaz:
http://arxiv.org/abs/1909.02352
Publikováno v:
IEEE Access, Vol 8, Pp 167319-167327 (2020)
Statistical models for predicting potential laying pattern were important for economically optimal breeding strategy of egg production in a poultry flock. The aim of this study was to establish an optimal model for describing egg production using roo
Externí odkaz:
https://doaj.org/article/1709212dba694486963abd8f12641899
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