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Airport Detection dgq Computer Vision Dataset

bydylTask:
Object Detection
License:CC BY 4.01.36k views42 downloads
See all 746 imagesAirport Detection dgq plane-vehicle-person-bird-u9R1 sample showing planeAirport Detection dgq plane-vehicle-person-bird-u9R1 sample showing planeAirport Detection dgq plane-vehicle-person-bird-u9R1 sampleAirport Detection dgq plane-vehicle-person-bird-u9R1 sampleAirport Detection dgq plane-vehicle-person-bird-u9R1 sampleAirport Detection dgq plane-vehicle-person-bird-u9R1 sample showing planeAirport Detection dgq plane-vehicle-person-bird-u9R1 sampleAirport Detection dgq plane-vehicle-person-bird-u9R1 sampleAirport Detection dgq plane-vehicle-person-bird-u9R1 sampleAirport Detection dgq plane-vehicle-person-bird-u9R1 sample showing planeAirport Detection dgq plane-vehicle-person-bird-u9R1 sampleAirport Detection dgq plane-vehicle-person-bird-u9R1 sample

About Airport Detection dgq Dataset

Here are a few use cases for this project:

  1. Air Traffic Management: The model could be deployed in air traffic control systems to automate the process of identifying and tracking planes, vehicles and people on the airstrip. This would improve the accuracy and efficiency of air traffic management and enhance safety protocols.

  2. Intelligent Surveillance: This model may be used for enhancing airport security systems by automatically detecting suspicious activities, unauthorised vehicles or persons and triggering alerts. It can also be used to monitor bird activity near airports to prevent bird strikes, which can be dangerous.

  3. Airport Operative Efficiency: The model can be employed by airlines and airport management to optimise ground operations by tracking the movement of ground vehicles, aircraft schedules, and personnel’s workflow.

  4. Wildlife Habitat Management: The model could be utilized to track bird activity patterns around airports. This data could assist in managing local habitats to minimize bird strikes and reduce the risk to aviation operations.

  5. Drone Monitoring & Control Systems: The model might be applied to drone technology aimed at monitoring and inspecting airport infrastructure including the airport apron, runways, terminals etc. It would help detect any obstacles including vehicles, people and especially birds.

Use Free Vehicle and Plane Detection API

Powered by general detection model

Code
pip install inference-sdk
# 1. Import the library
from inference_sdk import InferenceHTTPClient

# 2. Connect to your workspace
client = InferenceHTTPClient(
  api_url="https://serverless.roboflow.com",
  api_key="API_KEY"
)

# 3. Run your workflow on an image
result = client.run_workflow(
  workspace_name="<YOUR_WORKSPACE>",
  workflow_id="<YOUR_WORKFLOW_ID>",
  images={
    "image": "YOUR_IMAGE.jpg"  # Path to your image file
  },
  parameters={
    "classes": "vehicle, plane"
  },
  use_cache=True  # cache workflow definition for 15 minutes
)

# 4. Get your results
print(result)

Run on custom image

Drop an image here or click to upload

Detecting classes:
Or try a test image 

Cite This Project

LicenseCC BY 4.0

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

@misc{ airport-detection-dgq-jnkka_dataset,
  title = { Airport Detection dgq Dataset },
  type = { Open Source Dataset },
  author = { dyl },
  howpublished = { \url{ https://universe.roboflow.com/dyl-4eef8/airport-detection-dgq-jnkka } },
  url = { https://universe.roboflow.com/dyl-4eef8/airport-detection-dgq-jnkka },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2025 },
  month = { sep },
  note = { visited on 2026-07-29 },
}

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