segmentation_road Computer Vision Project
Updated 2 years ago
Metrics
Here are a few use cases for this project:
-
Autonomous Vehicle Navigation: The "segmentation_road" model can be incredibly useful for autonomous vehicles to identify and navigate through different kinds of road patterns which will ultimately contribute to better decisions while on the commute (like turning or changing lanes).
-
Traffic Management Systems: Implementing this model can help traffic management systems understand and predict the flow of traffic in different road patterns, improving congestion management, and implementing dynamic traffic signal controls.
-
Urban Planning: Understanding roads' layout using this model can assist city planners and architects when planning city infrastructures, ensuring a more efficient and safer road system.
-
Road Maintenance and Monitoring: The model can be used by city services to monitor road conditions, identify road degradation over time and prioritize maintenance and repairs.
-
Virtual Reality (VR) & Gaming: In the development of VR applications or games, this model can help in creating more realistic virtual environments by distinguishing various road layout patterns.
Use This Trained Model
Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
segmentation_road_dataset,
title = { segmentation_road Dataset },
type = { Open Source Dataset },
author = { image segmentation },
howpublished = { \url{ https://universe.roboflow.com/image-segmentation-awhml/segmentation_road } },
url = { https://universe.roboflow.com/image-segmentation-awhml/segmentation_road },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { mar },
note = { visited on 2024-11-14 },
}