5 citations · 5 across the 2 of their papers we have counts for
2 papers
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.LG2021★ 5 cited
Towards a Safety Case for Hardware Fault Tolerance in Convolutional Neural Networks Using Activation Range Supervision
Florian Geissler, Syed Qutub, Sayanta Roychowdhury +6
Convolutional neural networks (CNNs) have become an established part of numerous safety-critical computer vision applications, including human robot interactions and automated driv…