Insufficiency-Driven DNN Error Detection in the Context of SOTIF on Traffic Sign Recognition Use Case
Author:
Affiliation:
1. RD ADAS Software Platform, Mercedes-Benz AG, Sindelfingen, Germany
2. Institute of Measurement and Sensor Technology, Technical University of Kaiserslautern, Kaiserslautern, Germany
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/8784355/9999144/10016638.pdf?arnumber=10016638
Reference46 articles.
1. Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles
2. Towards Dependability Metrics for Neural Networks
3. Traffic-Sign Detection and Classification in the Wild
4. Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
5. Towards Improved Testing For Deep Learning
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