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
Occupancy
Parking guidance and information
Transfer of learning
Transport engineering
Parking space
Computer science
Deep learning
Parking lot
Environmental science
Real-time computing
Artificial intelligence
Engineering
Civil engineering
Subject Areas
Smart Parking Systems Research
·Building and Construction ·Physical Sciences
Vehicle License Plate Recognition
·Media Technology ·Physical Sciences
Video Surveillance and Tracking Methods
·Computer Vision and Pattern Recognition ·Physical Sciences
Citations by Year
2021: 1
2022: 2
2023: 1
2024: 2
2025: 1
OpenAlex SDG Match
SDGs auto-classified by OpenAlex (score ≥ 0.4 shown).
Sustainable cities and communities 41%
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