Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Gulsum Alicioglu"'
Autor:
Gulsum Alicioglu, Bo Sun
Publikováno v:
AI, Vol 5, Iss 2, Pp 465-481 (2024)
Deep learning (DL) models have achieved state-of-the-art performance in many domains. The interpretation of their working mechanisms and decision-making process is essential because of their complex structure and black-box nature, especially for sens
Externí odkaz:
https://doaj.org/article/c5c8e3522d354dd2b4c7f4d386e62c1f
Autor:
Gulsum Alicioglu, Bo Sun
Publikováno v:
Computers & Graphics. 102:502-520
Deep learning (DL) models have achieved impressive performance in various domains such as medicine, finance, and autonomous vehicle systems with advances in computing power and technologies. However, due to the black-box structure of DL models, the d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::956373e3461b14ccc3383d6ace2a1929
https://doi.org/10.1016/j.cag.2021.09.002
https://doi.org/10.1016/j.cag.2021.09.002
Autor:
Paul Turner, Cameron Thatcher, Russell Binaco, Alex Lam, Gulsum Alicioglu, Anthony Breitzman, Bo Sun, Matthew Schofield
Malicious software is constantly being developed and improved, so detection and classification of malwareis an ever-evolving problem. Since traditional malware detection techniques fail to detect new/unknown malware, machine learning algorithms have
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a3dbcb3081782271dfb9a11e56fac8fd
Autor:
Matthew Schofield, Gulsum Alicioglu, Russell Binaco, Alex Lam, Bo Sun, Cameron Thatcher, Paul Turner
Publikováno v:
Computer Science & Information Technology (CS & IT).
Malicious software is constantly being developed and improved, so detection and classification of malicious applications is an ever-evolving problem. Since traditional malware detection techniques fail to detect new or unknown malware, machine learni
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1a0f37db20b985db23f6fb94e504db00
https://doi.org/10.5121/csit.2021.110106
https://doi.org/10.5121/csit.2021.110106
Publikováno v:
Sustainability; Volume 14; Issue 11; Pages: 6569
Traffic accidents are inevitable events that occur unexpectedly and unintentionally. Therefore, analyzing traffic data is essential to prevent fatal accidents. Traffic data analysis provided insights into significant factors and driver behavioral pat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b75519ff114ade07d3dab715f8a9390
https://doi.org/10.3390/su14116569
https://doi.org/10.3390/su14116569
Assessing Accident Risk using Ordinal Regression and Multinomial Logistic Regression Data Generation
Publikováno v:
IJCNN
Robust and accurate modeling of motor vehicle accident and injury severities have significant impact on transportation safety and economy. The capability to assess accident risk based on external driving conditions (e.g., weather, road condition, etc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f0dc9f492a0726b7c06bd7b1f6f2cf8
https://doi.org/10.1109/ijcnn48605.2020.9207105
https://doi.org/10.1109/ijcnn48605.2020.9207105
Publikováno v:
13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018 ISBN: 9783030041632
13th International Conference on Application of Fuzzy Systems and Soft Computing (ICAFS) -- AUG 27-28, 2018 -- Warsaw, POLAND WOS: 000461058100049 Organizations have been trying to achieve their goals considering the internal and external environment
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc23200d3d0cb41ee78c5177b2d279b5
https://hdl.handle.net/20.500.12587/7971
https://hdl.handle.net/20.500.12587/7971