Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Hussam J. Mohammed"'
Autor:
Ahmed Adil Nafea, Muthanna Mishlish, Ali Muwafaq Shaban Shaban, Mohammed M AL-Ani, Khattab M Ali Alheeti, Hussam J. Mohammed
Publikováno v:
Iraqi Journal for Computer Science and Mathematics, Vol 4, Iss 4 (2023)
A precise prediction of student performance is an important aspect within educational institutions to improve results and provide personalized support of students. However, the predication accuracy of student performance considers an open issue withi
Externí odkaz:
https://doaj.org/article/421adf0f1dfd4eafba54c5ea41df2bfb
Autor:
Hussam J. Mohammed, Shumoos Al-Fahdawi, Alaa S. Al-Waisy, Dilovan Asaad Zebari, Dheyaa Ahmed Ibrahim, Mazin Abed Mohammed, Seifedine Kadry, Jungeun Kim
Publikováno v:
Mathematics, Vol 10, Iss 19, p 3530 (2022)
Person re-identification has become an essential application within computer vision due to its ability to match the same person over non-overlapping cameras. However, it is a challenging task because of the broad view of cameras with a large number o
Externí odkaz:
https://doaj.org/article/2de25d4fc58b42c696c8bf27efe89116
Publikováno v:
International Journal of Intelligent Robotics and Applications
The bean leaves can be affected by several diseases, such as angular leaf spots and bean rust, which can cause big damage to bean crops and decrease their productivity. Thus, treating these diseases in their early stages can improve the quality and q
Publikováno v:
Expert Systems. 39
Coronavirus disease 2019 (COVID-19) has attracted significant attention of researchers from various disciplines since the end of 2019. Although the global epidemic situation is stabilizing due to vaccination, new COVID-19 cases are constantly being d
Publikováno v:
THE 2ND UNIVERSITAS LAMPUNG INTERNATIONAL CONFERENCE ON SCIENCE, TECHNOLOGY, AND ENVIRONMENT (ULICoSTE) 2021.
Publikováno v:
ARES
Mohammed, H, Clarke, N & Li, F 2018, Evidence identification in heterogeneous data using clustering . in ARES 2018 Proceedings of the 13th International Conference on Availability, Reliability and Security ., 35, Association for Computing Machinery (ACM), ARES 2018 International Conference on Availability, Reliability and Security, Hamburg, Germany, 27/08/18 . https://doi.org/10.1145/3230833.3233271
Mohammed, H, Clarke, N & Li, F 2018, Evidence identification in heterogeneous data using clustering . in ARES 2018 Proceedings of the 13th International Conference on Availability, Reliability and Security ., 35, Association for Computing Machinery (ACM), ARES 2018 International Conference on Availability, Reliability and Security, Hamburg, Germany, 27/08/18 . https://doi.org/10.1145/3230833.3233271
Digital forensics faces several challenges in examining and analyzing data due to an increasing range of technologies at people’s disposal. The investigators find themselves having to process and analyze many systems manually (e.g. PC, laptop, Smar
Publikováno v:
Journal of Digital Forensics, Security and Law.
The major challenges with big data examination and analysis are volume, complex interdependence across content, and heterogeneity. The examination and analysis phases are considered essential to a digital forensics process. However, traditional techn