What Does Really Count? Estimating Relevance of Corner Cases for Semantic Segmentation in Automated Driving-Reference-Cited by-同舟云学术

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What Does Really Count? Estimating Relevance of Corner Cases for Semantic Segmentation in Automated Driving

Published:2023-10-02 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
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Author:

Breitenstein Jasmin¹,Heidecker Florian²,Lyssenko Maria³,Bogdoll Daniel⁴,Bieshaar Maarten⁵,Zöllner J. Marius⁴,Sick Bernhard²,Fingscheidt Tim¹

Affiliation:

1. Technische Universität Braunschweig

2. University of Kassel

3. Robert Bosch GmbH

4. KIT

5. Bosch Center for Artificial Intelligence

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10350357/10350360/10350723.pdf?arnumber=10350723

Reference35 articles.

1. A Single-Stream Segmentation and Depth Prediction CNN for Autonomous Driving

2. Binary TTC: A Temporal Geofence for Autonomous Navigation

3. Risk Ranked Recall: Collision Safety Metric for Object Detection Systems in Autonomous Vehicles

4. Description of Corner Cases in Automated Driving: Goals and Challenges

5. One Ontology to Rule Them All: Corner Case Scenarios for Autonomous Driving

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Corner cases in machine learning processes;AI Perspectives & Advances;2024-01-02

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