dataset Computer Vision Project

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Classes (2)
COL
LAN

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Description

Here are a few use cases for this project:

  1. Navigation Systems: The "dataset" computer vision model can be used in navigation systems in vehicles or Aircraft Traffic Control, to accurately identify and differentiate between "COL" (Collision) and "LAN" (Land) visual signals. This could enhance the efficiency of these systems and increase safety.

  2. Video Game Development: The model can be used in the development of realistic video games where the AI identifies and reacts to different scenarios like collisions and landing based on the faisceau classes.

  3. Robotics and Automation: Robots can use the model to maneuver around obstacles, reducing the risk of collisions. It can also be used in landing drones accurately by identifying landing spots.

  4. Driver Assist Systems: The model can be incorporated into assistive driving technology to identify potential collisions and provide alerts or initiate preventative measures.

  5. AI Courses & Research: The "dataset" computer vision model can be used in educational settings or research institutes for studying AI behavior. It can provide a practical basis for understanding differences in object recognition and reaction.

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Cite This Project

LICENSE
CC BY 4.0

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

                        @misc{
                            dataset-cief2_dataset,
                            title = { dataset Dataset },
                            type = { Open Source Dataset },
                            author = { Ecole Nationale dIngnieurs de Monastir },
                            howpublished = { \url{ https://universe.roboflow.com/ecole-nationale-dingnieurs-de-monastir/dataset-cief2 } },
                            url = { https://universe.roboflow.com/ecole-nationale-dingnieurs-de-monastir/dataset-cief2 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-11-30 },
                            }