Robust Perception and Visual Understanding of Traffic Signs in the Wild
Author:
Affiliation:
1. 1ISL, HRL Laboratories, LLC, Malibu, CA, USA
2. Research and Development, General Motors, Warren, MI, USA
Funder
General Motors Corporation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/8784355/9999144/10194416.pdf?arnumber=10194416
Reference34 articles.
1. Insufficiency-Driven DNN Error Detection in the Context of SOTIF on Traffic Sign Recognition Use Case
2. A Cascaded R-CNN With Multiscale Attention and Imbalanced Samples for Traffic Sign Detection
3. A survey on Image Data Augmentation for Deep Learning
4. A Plausibility-Based Fault Detection Method for High-Level Fusion Perception Systems
5. Robust Traffic Sign Recognition Against Camera Failures
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