Lane Detection with Deep Learning: Methods and Datasets

被引:0
|
作者
Li, Junyan [1 ]
机构
[1] Shandong Univ, Sch Mech Elect & Informat Engn, Weihai 264209, Peoples R China
来源
INFORMATION TECHNOLOGY AND CONTROL | 2023年 / 52卷 / 02期
关键词
Lane Detection; Deep Learning; Convolutional Neural Network; Dataset;
D O I
10.5755/j01.itc.52.2.32841
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Lane detection problem has been considered as an important computer vision task in autonomous driving. While it has received massive research attention in the literature, the problem is not yet fully solved. In this paper, a comprehensive literature review for lane detection, especially those with deep learning models, is presented. Furthermore, the latest collection of lane detection datasets is presented. The research gap is further filled by proposing a novel lane detection dataset named MudLane, which focuses on the lane detection task on suburban roads.
引用
收藏
页码:297 / 308
页数:12
相关论文
共 50 条
  • [31] Evaluation of unsupervised optical flow methods for deep learning in real world datasets
    Marez, Diego
    Harguess, Josh
    GEOSPATIAL INFORMATICS IX, 2019, 10992
  • [32] Deep-learning-based counting methods, datasets, and applications in agriculture: a review
    Farjon, Guy
    Huijun, Liu
    Edan, Yael
    PRECISION AGRICULTURE, 2023, 24 (05) : 1683 - 1711
  • [33] Deep-learning-based counting methods, datasets, and applications in agriculture: a review
    Guy Farjon
    Liu Huijun
    Yael Edan
    Precision Agriculture, 2023, 24 : 1683 - 1711
  • [34] Deep-Learning-Based Anomaly Detection for Lane-Changing Decisions
    Wang, Sheng-Li
    Lin, Chien
    Boddupalli, Srivalli
    Lin, Chung-Wei
    Ray, Sandip
    2022 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2022, : 1536 - 1542
  • [35] Exploring the Impact of Deep Learning Models on Lane Detection Through Semantic Segmentation
    Kumar S.
    Pandey A.
    Varshney S.
    SN Computer Science, 5 (1)
  • [36] Lane Detection for Autonomous Vehicle in Hazy Environment with Optimized Deep Learning Techniques
    Kumar, Bagesh
    Gupta, Harshit
    Sinha, Ayush
    Vyas, O. P.
    ADVANCED NETWORK TECHNOLOGIES AND INTELLIGENT COMPUTING, ANTIC 2021, 2022, 1534 : 596 - 608
  • [37] LLDNet: A Lightweight Lane Detection Approach for Autonomous Cars Using Deep Learning
    Khan, Md Al-Masrur
    Haque, Md Foysal
    Hasan, Kazi Rakib
    Alajmani, Samah H.
    Baz, Mohammed
    Masud, Mehedi
    Abdullah-Al Nahid
    SENSORS, 2022, 22 (15)
  • [38] CenFind: a deep-learning pipeline for efficient centriole detection in microscopy datasets
    Burgy, Leo
    Weigert, Martin
    Hatzopoulos, Georgios
    Minder, Matthias
    Journe, Adrien
    Rahi, Sahand Jamal
    Gonczy, Pierre
    BMC BIOINFORMATICS, 2023, 24 (01)
  • [39] Deep learning for cyber security intrusion detection: Approaches, datasets, and comparative study
    Ferrag, Mohamed Amine
    Maglaras, Leandros
    Moschoyiannis, Sotiris
    Janicke, Helge
    JOURNAL OF INFORMATION SECURITY AND APPLICATIONS, 2020, 50
  • [40] Revisiting the Performance of Deep Learning-Based Vulnerability Detection on Realistic Datasets
    Chakraborty, Partha
    Arumugam, Krishna Kanth
    Alfadel, Mahmoud
    Nagappan, Meiyappan
    McIntosh, Shane
    IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2024, 50 (08) : 2163 - 2177