Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Shonda Bernadin"'
Autor:
Xuanchen Xiang, Ruisheng Diao, Shonda Bernadin, Simon Y. Foo, Fangyuan Sun, Ayodeji S. Ogundana
Publikováno v:
IEEE Access, Vol 12, Pp 44080-44090 (2024)
Precise modeling of power systems is vital to ensure stability, reliability, and secure operations. In power industrial settings, model parameters can become skewed over time due to prolonged device usage or modifications made to the control systems.
Externí odkaz:
https://doaj.org/article/7f6e8b9bca9e4b0b948888b5c3f4b07d
Autor:
Isaac Ogunrinde, Shonda Bernadin
Publikováno v:
Sensors, Vol 24, Iss 14, p 4692 (2024)
The presence of fog in the background can prevent small and distant objects from being detected, let alone tracked. Under safety-critical conditions, multi-object tracking models require faster tracking speed while maintaining high object-tracking ac
Externí odkaz:
https://doaj.org/article/929aafdf5c4a4026b3721077151c5ada
Autor:
Prateek Mehta, Mubarak A. Mujawar, Samantha Lafrance, Shonda Bernadin, Daniel Ewing, Shekhar Bhansali
Publikováno v:
ECS Sensors Plus, Vol 3, Iss 3, p 030602 (2024)
Additive manufacturing in the realm of 3D printing has transformed the manufacturing sector, providing unmatched freedom in design and rapid prototyping abilities. However, a significant obstacle hindering its broader acceptance is the susceptibility
Externí odkaz:
https://doaj.org/article/eccd62d2c96d4fad9281c8edc76f1991
Autor:
Isaac Ogunrinde, Shonda Bernadin
Publikováno v:
Sensors, Vol 23, Iss 14, p 6255 (2023)
AVs are affected by reduced maneuverability and performance due to the degradation of sensor performances in fog. Such degradation can cause significant object detection errors in AVs’ safety-critical conditions. For instance, YOLOv5 performs well
Externí odkaz:
https://doaj.org/article/1ccf14fad712405692a597b63a338ff2
Publikováno v:
IEEE Access, Vol 9, Pp 64487-64498 (2021)
Facial expression recognition (FER) is a promising but challenging area of Computer Vision (CV). Many researchers have devoted significant resources to exploring FER in recent years, but an impediment remains: classifiers perform well on fine resolut
Externí odkaz:
https://doaj.org/article/cf55273f942d47ee810baef8b035e098
AVs suffer reduced maneuverability and performance due to the degradation in sensor performances in fog. Such degradation causes significant object detection errors essential for AVs' safety-critical conditions. For instance, YOLOv5 performs signific
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0424a2a65c136375acc117c6e4996490
https://doi.org/10.20944/preprints202305.2180.v1
https://doi.org/10.20944/preprints202305.2180.v1
Publikováno v:
Proceedings of the Future Technologies Conference (FTC) 2022, Volume 2 ISBN: 9783031184574
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b8e0a9c527c5497cc48789698e77e56
https://doi.org/10.1007/978-3-031-18458-1_1
https://doi.org/10.1007/978-3-031-18458-1_1
Publikováno v:
Practice and Experience in Advanced Research Computing.
Publikováno v:
IEEE Access, Vol 9, Pp 64487-64498 (2021)
Facial expression recognition (FER) is a promising but challenging area of Computer Vision (CV). Many researchers have devoted significant resources to exploring FER in recent years, but an impediment remains: classifiers perform well on fine resolut
Publikováno v:
SoutheastCon 2021.
Virtual Reality (VR) has become one of the emerging technologies over the past decade for improving the quality of life in human experiences. It has exciting and popular applications in entertainment, sports, education, and even digital documentation