ms_thesis Computer Vision Project

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Updated 13 days ago

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Description

Here are a few use cases for this project:

  1. Wildlife Monitoring and Conservation: Use the "ms_thesis" model to automatically identify and classify birds and flying objects in recorded footage from natural habitats. This can help researchers track bird species, their migration patterns, and monitor wildlife populations, while also detecting potential intrusions of drones or other aircraft in protected areas.

  2. Airport Safety and Security: Implement the model in surveillance systems around airports to detect and track various flying objects such as birds, drones, helicopters, and planes. Early detection of potential hazards can help reduce bird strikes and prevent unauthorized drones from entering restricted airspace, thus enhancing overall airport safety.

  3. Drone Traffic Management: Integrate the "ms_thesis" model into drone management systems to monitor and manage drone traffic in shared airspace. By accurately identifying and classifying drones, planes, and helicopters, the model can contribute to a more organized and controlled airspace, reducing the risk of accidents or collisions.

  4. Birdwatching and Citizen Science: Incorporate the "ms_thesis" model into birdwatching apps and platforms, enabling enthusiasts to better identify bird species in the field. Additionally, these identified sightings can be crowd-sourced to contribute valuable data for research and conservation efforts.

  5. Search and Rescue Operations: Utilize the model in search and rescue missions by deploying drones equipped with the "ms_thesis" model's computer vision capabilities. Identification of other drones, helicopters, and aircraft can help coordinate efforts while differentiating between targeted individuals and native bird species within the search area.

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Cite This Project

LICENSE
Public Domain

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

                        @misc{
                            ms_thesis-iivhe_dataset,
                            title = { ms_thesis Dataset },
                            type = { Open Source Dataset },
                            author = { Try },
                            howpublished = { \url{ https://universe.roboflow.com/try-ctwxt/ms_thesis-iivhe } },
                            url = { https://universe.roboflow.com/try-ctwxt/ms_thesis-iivhe },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { oct },
                            note = { visited on 2024-11-01 },
                            }
                        
                    

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