dna2 Instance Segmentation Dataset and Pre-Trained Model by Younghan Kim

Images

5000 images

Explore Dataset

Here are a few use cases for this project:

Precision Agriculture: dna2 can help farmers identify and assess the health of their crops by detecting positive vegetation in fields. This information can enable them to optimize irrigation, fertilization, and pest management, resulting in higher yields and more sustainable practices.
Environmental Monitoring: The model can be utilized by environmental organizations and researchers to monitor the coverage and growth of positive vegetation in various ecosystems. This can help track the impact of climate change, deforestation, and other ecological disturbances on plant life.
Urban Greenery Assessment: City planners and landscape architects can use dna2 to analyze satellite or aerial images of urban areas, identifying green spaces and positive vegetation. This could inform the development of greener city infrastructure and promote the value of parks and public gardens for ecological balance.
Land Use Classification: The model can aid in classifying different types of land, providing essential information for urban planning or natural resource management. By identifying areas of positive vegetation, this can help determine the borders between agricultural fields, protected natural spaces, and urban developments.
Disaster Recovery Assistance: In the aftermath of natural disasters, such as floods or wildfires, dna2 can help emergency response teams and aid organizations monitor and assess the damage to local vegetation. This information is crucial for the efficient allocation of resources and the formulation of restoration plans to revive damaged ecosystems.

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{
                            dna2-4gdaa_dataset,
                            title = { dna2 Dataset },
                            type = { Open Source Dataset },
                            author = { Younghan Kim },
                            howpublished = { \url{ https://universe.roboflow.com/younghan-kim-whxpt/dna2-4gdaa } },
                            url = { https://universe.roboflow.com/younghan-kim-whxpt/dna2-4gdaa },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { dec },
                            note = { visited on 2024-04-20 },
                            }