8 citations · 16 across the 6 of their papers we have counts for
7 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…
Targetless Rotational Auto-Calibration of Radar and Camera for Intelligent Transportation Systems
Christoph Schöller, Maximilian Schnettler, Annkathrin Krämmer +4
Most intelligent transportation systems use a combination of radar sensors and cameras for robust vehicle perception. The calibration of these heterogeneous sensor types in an auto…
Deep Anticipation: Light Weight Intelligent Mobile Sensing in IoT by Recurrent Architecture
Guang Chen, Shu Liu, Kejia Ren +4
The rapid growth of IoT era is shaping the future of mobile services. Advanced communication technology enables a heterogeneous connectivity where mobile devices broadcast informat…
Neural Networks for Safety-Critical Applications - Challenges, Experiments and Perspectives
Chih-Hong Cheng, Frederik Diehl, Yassine Hamza +5
We propose a methodology for designing dependable Artificial Neural Networks (ANN) by extending the concepts of understandability, correctness, and validity that are crucial ingred…