Research of Lane Detection Method Based on Attention Mechanism

DOI

10.2991/978-94-6463-002-2_8How to use a DOI?

Keywords

Deep learning; Semantic segmentation; Spatial attentional mechanism; Lane detection

Abstract

Facing the problems of low accuracy and poor real-time performance in lane detection, a lane detection method based on deep learning was proposed. ENet, a lightweight semantic segmentation network, is used as the backbone of the detection method. In view of the slender characteristics of lane lines, an improved spatial attention module is introduced to enhance the ability to extract lane line features. Then the final detection result is obtained by post-processing operation. Compared with SCNN and ENet, the improved algorithm has better accuracy and meets the requirements of real-time detection.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Lin Wang
AU  - Rongyu Lv
PY  - 2022
DA  - 2022/11/10
TI  - Research of Lane Detection Method Based on Attention Mechanism
BT  - Proceedings of the 2nd International Conference on Artificial Intelligence and Cloud Computing (ICAICC 2022)
PB  - Atlantis Press
SP  - 60
EP  - 66
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-002-2_8
DO  - 10.2991/978-94-6463-002-2_8
ID  - Wang2022
ER  -