Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Jianbin Mai"'
Publikováno v:
Big Data Mining and Analytics, Vol 6, Iss 4, Pp 391-403 (2023)
With the rapid development of mobile devices, aggregation security and efficiency topics are more important than past in crowd sensing. When collecting large-scale vehicle-provided data, the data transmitted via autonomous networks are publicly acces
Externí odkaz:
https://doaj.org/article/b522007bc50d401aa40d61b47327440d
Akademický článek
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Publikováno v:
Physical Communication. 56:101940
Publikováno v:
Materials Letters. 254:254-257
The behaviors of melting AgNO3 on original and poly(acrylic acid)-coated Al2O3 substrates were studied through in-situ observations. The spreading of AgNO3 flux on polymer-coated substrate was confined by “pinned” rim and high-resolution inkjet-p
Publikováno v:
2021 IEEE 6th International Conference on Big Data Analytics (ICBDA).
Aiming at the existing malware variants detection method based on deep convolutional neural networks (DCNN) has the problem of large computational resource consumption, a decomposing deep neural network (Dec-DCNN) is proposed for optimization. The co
Publikováno v:
Cyberspace Safety and Security ISBN: 9783030736705
CSS
CSS
Being able to detect malware variants is an important problem due to the rapid development and the security threats of new malware variations. Machine learning methods are currently one of the most popular malware variant detection methods, however,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81b5ebded449c3db3b1c6bbbfb013def
https://doi.org/10.1007/978-3-030-73671-2_7
https://doi.org/10.1007/978-3-030-73671-2_7
Publikováno v:
Cyberspace Safety and Security ISBN: 9783030736705
CSS
CSS
Deep neural networks (DNNs) have been found to be easily mislead by adversarial examples that add small perturbations to inputs to produce false results. Different attack and defense strategies have been proposed to better study the security of deep
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::003c6be2ff19a098732979a6c888731a
https://doi.org/10.1007/978-3-030-73671-2_8
https://doi.org/10.1007/978-3-030-73671-2_8
Publikováno v:
2020 5th IEEE International Conference on Big Data Analytics (ICBDA).
Intrusion detection system based on representation learning is the main research direction in the field of anomaly detection. Malicious traffic detection system can distinguish normal and malicious traffic by learning representations between normal a
Publikováno v:
Journal of Physics: Conference Series. 1993:012035
Aiming at the problem of large computational resource consumption in the existing object detection network for driver smoking detection, a decomposing YOLOv5 network (Dec-YOLOv5) is proposed for optimization. This method uses singular value decomposi