KNU_Parking_Detect_System Object Detection Dataset and Pre-Trained Model by KNU

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Explore Dataset

Here are a few use cases for this project:

Smart Parking Management: Automated systems can leverage this model to monitor and manage parking availability in real-time in large-scale places like shopping malls, airports, or city-wide parking lots.
Traffic Control and Navigation: Navigation apps or in-car navigation systems can use this model to provide drivers with real-time information about available parking spaces, improving efficiency and reducing congestion caused by cars looking for parking spots.
Security Enforcement: Surveillance systems can use this model to detect any unauthorized use of parking spaces or to track any suspicious movement or activity in parking areas.
Smart City Planning: The model can be used by city planners to better understand parking usage patterns and occupancy rates, assisting in designing more efficient and environmentally friendly city infrastructures.
Retail Analysis: Businesses can use this model to understand customer behavior by analyzing parking lot usage. This information can be used for optimizing business hours, staffing needs, or even predicting peak shopping times.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            knu_parking_detect_system_dataset,
                            title = { KNU_Parking_Detect_System Dataset },
                            type = { Open Source Dataset },
                            author = { KNU },
                            howpublished = { \url{ https://universe.roboflow.com/knu-jcqwu/knu_parking_detect_system } },
                            url = { https://universe.roboflow.com/knu-jcqwu/knu_parking_detect_system },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-04-27 },
                            }