Zobrazeno 1 - 10
of 62
pro vyhledávání: '"Gurcan Comert"'
Autor:
Cuthbert Ruseruka, Judith Mwakalonge, Gurcan Comert, Saidi Siuhi, Frank Ngeni, Quincy Anderson
Publikováno v:
Machine Learning with Applications, Vol 16, Iss , Pp 100547- (2024)
Detection and estimation of pothole dimensions is an essential step in road maintenance. Aging, heavy rainfall, traffic, and weak underlying layers may cause pavement potholes. Potholes can cause accidents when drivers lose control after hitting or s
Externí odkaz:
https://doaj.org/article/30d6e237099a403a85419bbe5904d4f5
Autor:
Tumlumbe Juliana Chengula, Judith Mwakalonge, Gurcan Comert, Methusela Sulle, Saidi Siuhi, Eric Osei
Publikováno v:
Machine Learning with Applications, Vol 17, Iss , Pp 100580- (2024)
The recent advancements in Advanced Driver Assistance Systems (ADAS) have significantly contributed to road safety and driving comfort. An integral aspect of these systems is the detection of driver anomalies such as drowsiness, distraction, and impa
Externí odkaz:
https://doaj.org/article/a5885684e5684d5ba4502f44f78b30de
Publikováno v:
Transportation Research Interdisciplinary Perspectives, Vol 24, Iss , Pp 101061- (2024)
The Coronavirus Disease 2019 (COVID-19) pandemic has considerably influenced school transportation in the United States (US), with conventional bus use declining and private vehicle use growing. It has increased traffic congestion, reliance on privat
Externí odkaz:
https://doaj.org/article/59b227c7c82b48b4b44b5162fcd16dd6
Publikováno v:
Machine Learning with Applications, Vol 15, Iss , Pp 100530- (2024)
Machine learning models for near collision detection in autonomous vehicles promise enhanced predictive power. However, training on these large datasets presents storage and computational challenges, particularly when operated on conventional computi
Externí odkaz:
https://doaj.org/article/8cf6aaeea5f5479ca0bc26c0f7b299bb
Autor:
Reek Majumder, Jacquan Pollard, M Sabbir Salek, David Werth, Gurcan Comert, Adrian Gale, Sakib Mahmud Khan, Samuel Darko, Mashrur Chowdhury
Publikováno v:
Environmental Health Insights, Vol 18 (2024)
The environmental impacts of global warming driven by methane (CH 4 ) emissions have catalyzed significant research initiatives in developing novel technologies that enable proactive and rapid detection of CH 4 . Several data-driven machine learning
Externí odkaz:
https://doaj.org/article/afdb6c6bd09b4b8ba51a72d3bc4ac62e
Autor:
Frank Ngeni, Judith Mwakalonge, Gurcan Comert, Saidi Siuhi, Tumlumbe Juliana Chengula, Cuthbert Ruseruka
Publikováno v:
Transportation Research Interdisciplinary Perspectives, Vol 23, Iss , Pp 101012- (2024)
Pediatric Vehicular Heatstroke (PVH) has been among the leading cause of non-traffic deaths among kids in the US. According to NHTSA, more than 900 children have died since 1998 because of being left in cars or accessing the cars without notice by ad
Externí odkaz:
https://doaj.org/article/03a861138de84941ad187f2e895e3715
Publikováno v:
Machine Learning with Applications, Vol 14, Iss , Pp 100510- (2023)
The adoption of Advanced Driver Assistance Systems (ADAS) has expanded dramatically in recent years, with the goal of improving road safety and driving comfort. Driver monitoring is important to ADAS since it identifies abnormalities such as sleepine
Externí odkaz:
https://doaj.org/article/f81c441df38c42119245fdb524bf9849
Publikováno v:
Vehicles, Vol 5, Iss 3, Pp 931-948 (2023)
Road authorities worldwide can leverage the advances in vehicle technology by continuously monitoring their roads’ conditions to minimize road maintenance costs. The existing methods for carrying out road condition surveys involve manual observatio
Externí odkaz:
https://doaj.org/article/a16f335149c8472295465c7c3add7d51
Publikováno v:
Vehicles, Vol 5, Iss 2, Pp 565-582 (2023)
Road hazards are one of the significant sources of fatalities in road accidents. The accurate estimation of road hazards can ensure safety and enhance the driving experience. Existing methods of road condition monitoring are time-consuming, expensive
Externí odkaz:
https://doaj.org/article/ed2671faf7b44af4a95bb63dbcf6c00d
Autor:
Gurcan Comert, Negash Begashaw
Publikováno v:
International Journal of Transportation Science and Technology, Vol 11, Iss 2, Pp 283-297 (2022)
Estimation models from connected vehicles often assume low level parameters such as arrival rates and market penetration rates as known or estimate them in real-time. At low market penetration rates, such parameter estimators produce large errors mak
Externí odkaz:
https://doaj.org/article/b41d49bda83c4488bd2f6d7fa31c87b3