Lane detection is an important part of car autopilot. It helps the vehicle to stabilize itself in the lane, avoid risks, and determine the direction of driving. In this paper, we propose a neural network approach to detect lanes in different conditions. We also collect 1761 frames of front-view pictures from driving recorders, preprocess them with ROI analysis as training and testing data. Resulted models have overall high accuracy over tests.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Lane Detection Based on DeepLab


    Additional title:

    Advs in Intelligent Syst., Computing


    Contributors:
    Liu, Qi (editor) / Liu, Xiaodong (editor) / Li, Lang (editor) / Zhou, Huiyu (editor) / Zhao, Hui-Huang (editor) / Li, Mingzhe (author)


    Publication date :

    2020-07-01


    Size :

    7 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    DMA-Net: DeepLab With Multi-Scale Attention for Pavement Crack Segmentation

    Sun, Xinzi / Xie, Yuanchang / Jiang, Liming et al. | IEEE | 2022


    Comparison of Deep Learning Algorithms UNet and DeepLab for Oil Palm Plantation Mapping With Semantic Segmentation Approach

    Gates Siallagan, Mark Bill / Salim, Sunarko / Putra Ananda Muslim, Reyhan Tri et al. | IEEE | 2024


    LANE DETECTION DEVICE AND LANE DETECTION METHOD

    OKANO KENJI | European Patent Office | 2016

    Free access

    Perspective Transform-Based Lane Detection for Lane Keep Assistance

    Gireesha, H. M. / Aarya, K. H. / Sahana, B. S. et al. | Springer Verlag | 2024


    Lane detection apparatus and lane detection method

    OKANO KENJI | European Patent Office | 2018

    Free access