Test_data_BG Object Detection Dataset and Pre-Trained Model by Texas AM University

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Explore Dataset

Here are a few use cases for this project:

Agriculture Optimization: Farmers could use the model to detect and classify different types of weeds in their fields, such as poa, enabling them to tackle and manage weeds more accurately and improve their crop yield.
Park and Recreational Areas Maintenance: The model can be used by city park departments to identify weed types in public recreational spaces. This way, they can optimally target their weed maintenance efforts in line with the specific types of weeds detected.
Supply Chain Optimization in Weed Control Products: Companies producing weed control products could utilize this model during product testing phase to identify the efficacy of their product on different weed types like poa.
Biodiversity Studies: Research organizations studying plant biodiversity can use the model to automatically classify and identify various weed species in different habitats, contributing to a better understanding of weed distribution and their impact on local ecosystems.
Landscape Management: The model can assist landscape architects or gardeners in identifying and managing weed types in their designs, contributing to more time and cost-efficient maintenance.

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{
                            test_data_bg_dataset,
                            title = { Test_data_BG Dataset },
                            type = { Open Source Dataset },
                            author = { Texas AM University },
                            howpublished = { \url{ https://universe.roboflow.com/texas-am-university/test_data_bg } },
                            url = { https://universe.roboflow.com/texas-am-university/test_data_bg },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jul },
                            note = { visited on 2024-05-06 },
                            }