A Comparison of Hough Transform and Deep Neural Network Methods on Road Segmentation

Sidika Elbi Mutluoglu, Tamer Olmez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Thanks to developments in the computer hardware systems, deep learning has been an attractive field for many researchers in different disciplines. Aim of deep learning is to extract the desired features of raw data as a learning method by operating many hidden layers. Accomplished results of learning methods on complex issues as face recognition, object detection, motion recognition etc. led researchers to think about applying deep learning methods to road lane detection-segmentation which is one of the very important issues of Advanced Driver Assistance Systems (ADAS). Considering main limitations of conventional methods for lane detection, deep learning approach can provide more robustness than existing approaches. The objective of work is to compare the effectiveness of conventional and deep learning applications to improve accuracy of the road segmentation.

Original languageEnglish
Title of host publication3rd International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728137896
DOIs
Publication statusPublished - Oct 2019
Event3rd International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2019 - Ankara, Turkey
Duration: 11 Oct 201913 Oct 2019

Publication series

Name3rd International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2019 - Proceedings

Conference

Conference3rd International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2019
Country/TerritoryTurkey
CityAnkara
Period11/10/1913/10/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Funding

ACKNOWLEDGMENT This work is supported by AVL Autonomous Drive & Vehicle Controls Team. We would like to thank Ahmetcan

FundersFunder number
AVL List

    Keywords

    • ADAS
    • Deep Learning
    • Deep Neural Networks
    • Image Processing
    • Lane Detection
    • Machine Learning

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