no code implementations • 13 May 2024 • Hakan Yekta Yatbaz, Mehrdad Dianati, Konstantinos Koufos, Roger Woodman
The deep neural network (DNN) models are widely used for object detection in automated driving systems (ADS).
no code implementations • 11 Apr 2024 • Hakan Yekta Yatbaz, Mehrdad Dianati, Konstantinos Koufos, Roger Woodman
To address the real-time operation requirements in ADS, we also introduce a novel introspection method that combines activation patterns from multiple layers of the detector's backbone and report its performance.
no code implementations • 2 Mar 2024 • Hakan Yekta Yatbaz, Mehrdad Dianati, Konstantinos Koufos, Roger Woodman
The proposed approach pre-processes the neural activation patterns of the object detector's backbone using several different modes.
1 code implementation • 19 Sep 2023 • Mreza Alipour Sormoli, Amir Samadi, Sajjad Mozaffari, Konstantinos Koufos, Mehrdad Dianati, Roger Woodman
Anticipating the motion of other road users is crucial for automated driving systems (ADS), as it enables safe and informed downstream decision-making and motion planning.