Evaluating State-of-the-Art Object Detector on Challenging Traffic Light Data-Reference-Cited by-同舟云学术

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Evaluating State-of-the-Art Object Detector on Challenging Traffic Light Data

Published:2017-07 Issue: Volume: Page:
ISSN:
Container-title:2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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Author:

Jensen Morten B.,Nasrollahi Kamal,Moeslund Thomas B.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8014302/8014734/08014856.pdf?arnumber=8014856

Cited by 53 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. Traffic Signal Detection and Recognition Algorithms for Autonomous Vehicles: A Brief Review;Journal of Transportation Engineering, Part A: Systems;2024-10

2. Traffic Light Detection and Recognition using Ensemble Learning with Color-Based Data Augmentation;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

3. A Coarse-to-Fine Deep Learning Based Framework for Traffic Light Recognition;IEEE Transactions on Intelligent Transportation Systems;2024

4. Advanced efficient strategy for detection of dark objects based on spiking network with multi-box detection;Multimedia Tools and Applications;2023-09-27

5. Traffic Light Recognition using Convolutional Neural Networks: A Survey;2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC);2023-09-24

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