A hybrid spatial–temporal deep learning architecture for lane detection-Reference-Cited by-同舟云学术

A hybrid spatial–temporal deep learning architecture for lane detection

Published:2022-02-20 Issue:1 Volume:38 Page:67-86
ISSN:1093-9687
Container-title:Computer-Aided Civil and Infrastructure Engineering
language:en
Short-container-title:Computer aided Civil Eng

Author:

Dong Yongqi¹,Patil Sandeep²,van Arem Bart¹,Farah Haneen¹

Affiliation:

1. Department of Transport and Planning, Faculty of Civil Engineering and Geosciences Delft University of Technology Delft The Netherlands

2. Faculty of Mechanical, Maritime and Materials Engineering Delft University of Technology Delft The Netherlands

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Science Applications,Civil and Structural Engineering,Building and Construction

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/mice.12829

Reference54 articles.

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2. A Novel Strategy for Road Lane Detection and Tracking Based on a Vehicle’s Forward Monocular Camera

3. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

4. Ballas N. Yao L. Pal C. &Courville A.(2016).Delving deeper into convolutional networks for learning video representations.4th International Conference on Learning Representations ICLR 2016–Conference Track Proceedings San Juan Puerto Rico.

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