Deep Learning-based Road Segmentation & Pedestrian Detection System for Intelligent Vehicles

Gozde Yolcu Öztel; İsmail Öztel

doi:10.35377/saucis...1170902

EN

Deep Learning-based Road Segmentation & Pedestrian Detection System for Intelligent Vehicles

Abstract

Correctly determining the driving area and pedestrians is crucial for intelligent vehicles to reduce fatal road accidents risk. But these are challenging tasks in the computer vision field. Various weather, road conditions, etc., make them difficult. This paper presents a vision-based road segmentation and pedestrian detection system. First, the roads are segmented using a deep learning based consecutive triple filter size (CTFS) approach. Then, pedestrians on the segmented roads are detected using the transfer learning approach. The CTFS approach can create feature maps for small and big features. The proposed system is a reliable, low-cost road segmentation and pedestrian detection system for intelligent vehicles.

Keywords

References

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Details

Primary Language

English

Subjects

Computer Software

Journal Section

Research Article

Authors

Gozde Yolcu Öztel ^*
0000-0002-7841-2131
Türkiye

İsmail Öztel
0000-0001-5157-7035
Türkiye

Early Pub Date

April 28, 2023

Publication Date

April 30, 2023

Submission Date

September 4, 2022

Acceptance Date

February 24, 2023

Published in Issue

Year 2023 Volume: 6 Number: 1

DOI

https://doi.org/10.35377/saucis...1170902

IZ

https://izlik.org/JA22TT89PC

Cite

RIS / Bibtex

APA

Yolcu Öztel, G., & Öztel, İ. (2023). Deep Learning-based Road Segmentation & Pedestrian Detection System for Intelligent Vehicles. Sakarya University Journal of Computer and Information Sciences, 6(1), 22-31. https://doi.org/10.35377/saucis...1170902

AMA

1.Yolcu Öztel G, Öztel İ. Deep Learning-based Road Segmentation & Pedestrian Detection System for Intelligent Vehicles. SAUCIS. 2023;6(1):22-31. doi:10.35377/saucis.1170902

Chicago

Yolcu Öztel, Gozde, and İsmail Öztel. 2023. “Deep Learning-Based Road Segmentation & Pedestrian Detection System for Intelligent Vehicles”. Sakarya University Journal of Computer and Information Sciences 6 (1): 22-31. https://doi.org/10.35377/saucis. 1170902.

EndNote

Yolcu Öztel G, Öztel İ (April 1, 2023) Deep Learning-based Road Segmentation & Pedestrian Detection System for Intelligent Vehicles. Sakarya University Journal of Computer and Information Sciences 6 1 22–31.

IEEE

[1]G. Yolcu Öztel and İ. Öztel, “Deep Learning-based Road Segmentation & Pedestrian Detection System for Intelligent Vehicles”, SAUCIS, vol. 6, no. 1, pp. 22–31, Apr. 2023, doi: 10.35377/saucis...1170902.

ISNAD

Yolcu Öztel, Gozde - Öztel, İsmail. “Deep Learning-Based Road Segmentation & Pedestrian Detection System for Intelligent Vehicles”. Sakarya University Journal of Computer and Information Sciences 6/1 (April 1, 2023): 22-31. https://doi.org/10.35377/saucis. 1170902.

JAMA

1.Yolcu Öztel G, Öztel İ. Deep Learning-based Road Segmentation & Pedestrian Detection System for Intelligent Vehicles. SAUCIS. 2023;6:22–31.

MLA

Yolcu Öztel, Gozde, and İsmail Öztel. “Deep Learning-Based Road Segmentation & Pedestrian Detection System for Intelligent Vehicles”. Sakarya University Journal of Computer and Information Sciences, vol. 6, no. 1, Apr. 2023, pp. 22-31, doi:10.35377/saucis. 1170902.

Vancouver

1.Gozde Yolcu Öztel, İsmail Öztel. Deep Learning-based Road Segmentation & Pedestrian Detection System for Intelligent Vehicles. SAUCIS. 2023 Apr. 1;6(1):22-31. doi:10.35377/saucis. 1170902