8 citations · 8 across the 4 of their papers we have counts for
4 papers
Global Clipper: Enhancing Safety and Reliability of Transformer-based Object Detection Models
Qutub Syed Sha, Michael Paulitsch, Karthik Pattabiraman +6
As transformer-based object detection models progress, their impact in critical sectors like autonomous vehicles and aviation is expected to grow. Soft errors causing bit flips dur…
Situation Monitor: Diversity-Driven Zero-Shot Out-of-Distribution Detection using Budding Ensemble Architecture for Object Detection
Qutub Syed, Michael Paulitsch, Korbinian Hagn +5
We introduce Situation Monitor, a novel zero-shot Out-of-Distribution (OOD) detection approach for transformer-based object detection models to enhance reliability in safety-critic…
BEA: Revisiting anchor-based object detection DNN using Budding Ensemble Architecture
Syed Sha Qutub, Neslihan Kose, Rafael Rosales +6
This paper introduces the Budding Ensemble Architecture (BEA), a novel reduced ensemble architecture for anchor-based object detection models. Object detection models are crucial i…
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…