Determining the Occupancy of Vehicle Parking Areas by Deep Learning

Ayse Betul Baktir; Bulent Bolat

doi:10.1109/ICECCE49384.2020.9179399

Determining the Occupancy of Vehicle Parking Areas by Deep Learning

Ayse Betul Baktir, Bulent Bolat

Yildiz Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

Parking a vehicle in heavy traffic situations leads to prolonged driving time, deterioration of traffic flow and therefore environmental pollution when searching for free space. Although the sensor systems in the indoor parking lots are beneficial, these systems cannot be applied to outdoor spaces. In this study, a deep learning application was developed which classifies the occupancy status of the parking spaces in outdoor parking areas. High accuracy rates were obtained in this application where transfer learning was performed using ResNet model.

Original language	English
Title of host publication	2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728171166
DOIs	https://doi.org/10.1109/ICECCE49384.2020.9179399
Publication status	Published - Jun 2020
Externally published	Yes
Event	2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020 - Istanbul, Turkey Duration: 12 Jun 2020 → 13 Jun 2020

Publication series

Name	2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020

Conference

Conference	2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020
Country/Territory	Turkey
City	Istanbul
Period	12/06/20 → 13/06/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

CNRPark
Deep Learning
Parking Lot
PKLot
ResNet

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ICECCE49384.2020.9179399

Cite this

Baktir, A. B., & Bolat, B. (2020). Determining the Occupancy of Vehicle Parking Areas by Deep Learning. In 2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020 Article 9179399 (2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICECCE49384.2020.9179399

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title = "Determining the Occupancy of Vehicle Parking Areas by Deep Learning",

abstract = "Parking a vehicle in heavy traffic situations leads to prolonged driving time, deterioration of traffic flow and therefore environmental pollution when searching for free space. Although the sensor systems in the indoor parking lots are beneficial, these systems cannot be applied to outdoor spaces. In this study, a deep learning application was developed which classifies the occupancy status of the parking spaces in outdoor parking areas. High accuracy rates were obtained in this application where transfer learning was performed using ResNet model.",

keywords = "CNRPark, Deep Learning, Parking Lot, PKLot, ResNet",

author = "Baktir, {Ayse Betul} and Bulent Bolat",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020 ; Conference date: 12-06-2020 Through 13-06-2020",

year = "2020",

month = jun,

doi = "10.1109/ICECCE49384.2020.9179399",

language = "English",

series = "2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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}

Baktir, AB & Bolat, B 2020, Determining the Occupancy of Vehicle Parking Areas by Deep Learning. in 2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020., 9179399, 2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020, Institute of Electrical and Electronics Engineers Inc., 2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020, Istanbul, Turkey, 12/06/20. https://doi.org/10.1109/ICECCE49384.2020.9179399

Determining the Occupancy of Vehicle Parking Areas by Deep Learning. / Baktir, Ayse Betul; Bolat, Bulent.
2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9179399 (2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Determining the Occupancy of Vehicle Parking Areas by Deep Learning

AU - Baktir, Ayse Betul

AU - Bolat, Bulent

PY - 2020/6

Y1 - 2020/6

N2 - Parking a vehicle in heavy traffic situations leads to prolonged driving time, deterioration of traffic flow and therefore environmental pollution when searching for free space. Although the sensor systems in the indoor parking lots are beneficial, these systems cannot be applied to outdoor spaces. In this study, a deep learning application was developed which classifies the occupancy status of the parking spaces in outdoor parking areas. High accuracy rates were obtained in this application where transfer learning was performed using ResNet model.

AB - Parking a vehicle in heavy traffic situations leads to prolonged driving time, deterioration of traffic flow and therefore environmental pollution when searching for free space. Although the sensor systems in the indoor parking lots are beneficial, these systems cannot be applied to outdoor spaces. In this study, a deep learning application was developed which classifies the occupancy status of the parking spaces in outdoor parking areas. High accuracy rates were obtained in this application where transfer learning was performed using ResNet model.

KW - CNRPark

KW - Deep Learning

KW - Parking Lot

KW - PKLot

KW - ResNet

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U2 - 10.1109/ICECCE49384.2020.9179399

DO - 10.1109/ICECCE49384.2020.9179399

M3 - Conference contribution

AN - SCOPUS:85091942037

T3 - 2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020

BT - 2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020

Y2 - 12 June 2020 through 13 June 2020

ER -

Baktir AB, Bolat B. Determining the Occupancy of Vehicle Parking Areas by Deep Learning. In 2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 9179399. (2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020). doi: 10.1109/ICECCE49384.2020.9179399

Determining the Occupancy of Vehicle Parking Areas by Deep Learning

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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