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Towards Dependability Metrics for Neural Networks

6 June 2018

Papers citing "Towards Dependability Metrics for Neural Networks"

20 / 20 papers shown

Title
Investigating Calibration and Corruption Robustness of Post-hoc Pruned Perception CNNs: An Image Classification Benchmark Study Pallavi Mitra Gesina Schwalbe Nadja Klein AAML 74 1 0 31 May 2024
A Survey of Neural Network Robustness Assessment in Image Recognition Jie Wang Jun Ai Minyan Lu Haoran Su Dan Yu Yutao Zhang Junda Zhu Jingyu Liu AAML 120 3 0 12 Apr 2024
Outline of an Independent Systematic Blackbox Test for ML-based Systems H. Wiesbrock Jürgen Grossmann 60 0 0 30 Jan 2024
PEM: Perception Error Model for Virtual Testing of Autonomous Vehicles A. Piazzoni Jim Cherian Justin Dauwels Lap-Pui Chau 55 12 0 23 Feb 2023
Backdoor Mitigation in Deep Neural Networks via Strategic Retraining Akshay Dhonthi E. M. Hahn Vahid Hashemi AAML 47 2 0 14 Dec 2022
Empowering the trustworthiness of ML-based critical systems through engineering activities J. Mattioli Agnès Delaborde Souhaiel Khalfaoui Freddy Lecue H. Sohier F. Jurie 36 2 0 30 Sep 2022
Exploring ML testing in practice -- Lessons learned from an interactive rapid review with Axis Communications Qunying Song Markus Borg Emelie Engström H. Ardö Sergio Rico 45 10 0 30 Mar 2022
Safe AI -- How is this Possible? Harald Ruess Simon Burton 65 0 0 25 Jan 2022
A causal model of safety assurance for machine learning Simon Burton CML 81 5 0 14 Jan 2022
Enabling Verification of Deep Neural Networks in Perception Tasks Using Fuzzy Logic and Concept Embeddings Gesina Schwalbe Christian Wirth Ute Schmid AAML 41 7 0 03 Jan 2022
Network Generalization Prediction for Safety Critical Tasks in Novel Operating Domains Molly O'Brien Michael Medoff Julia V. Bukowski Gregory Hager OOD 77 3 0 17 Aug 2021
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety Sebastian Houben Stephanie Abrecht Maram Akila Andreas Bär Felix Brockherde ... Serin Varghese Michael Weber Sebastian J. Wirkert Tim Wirtz Matthias Woehrle AAML 126 58 0 29 Apr 2021
Application of the Neural Network Dependability Kit in Real-World Environments Amit Sahu Noelia Vállez Rosana Rodríguez-Bobada Mohamad Alhaddad Omar Moured G. Neugschwandtner 17 2 0 14 Dec 2020
Coverage Guided Testing for Recurrent Neural Networks Wei Huang Youcheng Sun Xing-E. Zhao James Sharp Wenjie Ruan Jie Meng Xiaowei Huang AAML 126 48 0 05 Nov 2019
A Systematic Mapping Study on Testing of Machine Learning Programs S. Sherin Muhammad Uzair Khan Muhammad Zohaib Z. Iqbal 39 13 0 11 Jul 2019
Machine Learning Testing: Survey, Landscapes and Horizons Jie M. Zhang Mark Harman Lei Ma Yang Liu VLM AILaw 101 756 0 19 Jun 2019
Engineering problems in machine learning systems Hiroshi Kuwajima Hirotoshi Yasuoka Toshihiro Nakae 52 3 0 01 Apr 2019
A Survey of Safety and Trustworthiness of Deep Neural Networks: Verification, Testing, Adversarial Attack and Defence, and Interpretability Xiaowei Huang Daniel Kroening Wenjie Ruan Marta Kwiatkowska Youcheng Sun Emese Thamo Min Wu Xinping Yi AAML 132 51 0 18 Dec 2018
Traceability of Deep Neural Networks Vincent Aravantinos Frederik Diehl 61 12 0 17 Dec 2018
nn-dependability-kit: Engineering Neural Networks for Safety-Critical Autonomous Driving Systems Chih-Hong Cheng Chung-Hao Huang Georg Nührenberg 71 11 0 16 Nov 2018