Zobrazeno 1 - 6
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pro vyhledávání: '"Jumabek Alikhanov"'
Autor:
Jumabek Alikhanov, Hakil Kim
Publikováno v:
IEEE Access, Vol 11, Pp 68079-68092 (2023)
Online action detection in surveillance scenarios presents considerable challenges, particularly due to the dynamically changing environments and real-time processing requirements. Within this context, Multi-Object Tracking (MOT) serves as a critical
Externí odkaz:
https://doaj.org/article/16dc99f1dbe44ba58d51d6578851c16b
Autor:
Jumabek Alikhanov, Rhongho Jang, Mohammed Abuhamad, David Mohaisen, Daehun Nyang, Youngtae Noh
Publikováno v:
IEEE Access, Vol 10, Pp 5801-5823 (2022)
Machine Learning (ML) based Network Intrusion Systems (NIDSs) operate on flow features which are obtained from flow exporting protocols (i.e., NetFlow). Recent success of ML and Deep Learning (DL) based NIDS solutions assume such flow information (e.
Externí odkaz:
https://doaj.org/article/fc1c19fed78949fcb6af33d98885b242
Publikováno v:
IEEE Access, Vol 10, Pp 94249-94261 (2022)
The world’s elderly population continues to grow at an unprecedented rate, creating a need to monitor the safety of an aging population. One of the current problems is accurately classifying elderly physical activities, especially falling down, and
Externí odkaz:
https://doaj.org/article/d546f9fcc0754b7689f9a4b34d8ea400
Publikováno v:
IEEE Access. 10:94249-94261
Publikováno v:
2022 22nd International Conference on Control, Automation and Systems (ICCAS).
Publikováno v:
Electronics; Volume 11; Issue 4; Pages: 515
In the modern era of active network throughput and communication, the study of Intrusion Detection Systems (IDS) is a crucial role to ensure safe network resources and information from outside invasion. Recently, IDS has become a needful tool for imp