Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Zaid A. El Shair"'
Autor:
Zaid A. El Shair, Samir A. Rawashdeh
Publikováno v:
Data in Brief, Vol 58, Iss , Pp 111205- (2025)
In this data article, we introduce the Multi-Modal Event-based Vehicle Detection and Tracking (MEVDT) dataset. This dataset provides a synchronized stream of event data and grayscale images of traffic scenes, captured using the Dynamic and Active-Pix
Externí odkaz:
https://doaj.org/article/9b3883d8ed98437b8e9e911658cef92e
Publikováno v:
IEEE Access, Vol 11, Pp 102899-102916 (2023)
Event-based vision is a novel perception modality that offers several advantages, such as high dynamic range and robustness to motion blur. In order to process events in batches and utilize modern computer vision deep-learning architectures, an inter
Externí odkaz:
https://doaj.org/article/42a087a9f504403e97904c49defe2add
Publikováno v:
IEEE Access, Vol 9, Pp 114808-114820 (2021)
The automotive domain is highly regulated, with many safety-critical aspects to consider. This means that a great deal of testing is required to validate the performance of automotive systems, under all possible environmental conditions. For vision-b
Externí odkaz:
https://doaj.org/article/2ec20b8778a94c5792d35695cb041bfa
Publikováno v:
Journal of Imaging, Vol 10, Iss 9, p 227 (2024)
Road conditions, often degraded by insufficient maintenance or adverse weather, significantly contribute to accidents, exacerbated by the limited human reaction time to sudden hazards like potholes. Early detection of distant potholes is crucial for
Externí odkaz:
https://doaj.org/article/5299ef4af37042eeb1375e96bc3befa5