On Why the System Makes the Corner Case: AI-based Holistic Anomaly Detection for Autonomous Driving-Reference-Cited by-同舟云学术

On Why the System Makes the Corner Case: AI-based Holistic Anomaly Detection for Autonomous Driving

Published:2022-06-05 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Intelligent Vehicles Symposium (IV)
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Author:

Pfeil Jerg¹,Wieland Jochen¹,Michalke Thomas¹,Theissler Andreas²

Affiliation:

1. Robert Bosch GmbH, Robert-Bosch-Platz 1,Gerlingen-Schillerhohe,Germany,70839

2. Aalen University of Applied Sciences,Aalen,Germany,73430

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9826996/9826997/09827078.pdf?arnumber=9827078

Reference32 articles.

1. SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection;zhao;Proceedings of the 4th Conference on Machine Learning and Systems (MLSys),0

2. PyOD: A Python Toolbox for Scalable Outlier Detection;zhao;In 20 96,2019

3. Efficient Statistical Validation of Autonomous Driving Systems

4. Outlier Detection Using Replicator Neural Networks

5. Discovering cluster-based local outliers

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