19 citations · 39 across the 10 of their papers we have counts for
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cs.CV2022
Reliable Multimodal Trajectory Prediction via Error Aligned Uncertainty Optimization
Neslihan Kose, Ranganath Krishnan, Akash Dhamasia +2
Reliable uncertainty quantification in deep neural networks is very crucial in safety-critical applications such as automated driving for trustworthy and informed decision-making.…
cs.CV2022★ 8 cited
Hardware faults that matter: Understanding and Estimating the safety impact of hardware faults on object detection DNNs
Syed Qutub, Florian Geissler, Yang Peng +4
Object detection neural network models need to perform reliably in highly dynamic and safety-critical environments like automated driving or robotics. Therefore, it is paramount to…