Hardware faults that matter: Understanding and Estimating the safety impact of hardware faults on object detection DNNs

7 September 2022

Papers citing "Hardware faults that matter: Understanding and Estimating the safety impact of hardware faults on object detection DNNs"

7 / 7 papers shown

Title
Towards a Safety Case for Hardware Fault Tolerance in Convolutional Neural Networks Using Activation Range Supervision Florian Geissler S. Qutub S. Roychowdhury Ali Asgari Khoshouyeh Ya-li Peng Akash Dhamasia Ralf Graefe Karthik Pattabiraman Michael Paulitsch AAML 36 13 0 16 Aug 2021
Fault Injectors for TensorFlow: Evaluation of the Impact of Random Hardware Faults on Deep CNNs Michael Beyer Andrey Morozov E. Valiev Christoph Schorn Lydia Gauerhof K. Ding K. Janschek AAML 25 7 0 13 Dec 2020
Terminal Brain Damage: Exposing the Graceless Degradation in Deep Neural Networks Under Hardware Fault Attacks Sanghyun Hong Pietro Frigo Yigitcan Kaya Cristiano Giuffrida Tudor Dumitras AAML 53 211 0 03 Jun 2019
YOLOv3: An Incremental Improvement Joseph Redmon Ali Farhadi ObjD 105 21,386 0 08 Apr 2018
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.0K 193,426 0 10 Dec 2015
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks Shaoqing Ren Kaiming He Ross B. Girshick Jian Sun AIMat ObjD 473 62,122 0 04 Jun 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.5K 100,213 0 04 Sep 2014