Computer Vision Object Detection Dataset and Pre-Trained Model by Precision Drone Spray

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Explore Dataset

Here are a few use cases for this project:

Precision Agriculture: This computer vision model can be integrated into agricultural machinery and drones to autonomously identify and target weeds like Waterhemp for selective herbicide application or removal, leading to increased crop yields and reduced chemical usage.
Environmental Monitoring: Researchers and environmental agencies can utilize this model to assess the spread and prevalence of invasive weed species like Waterhemp in natural ecosystems, informing them about potential threats to local flora and guiding their intervention strategies.
Land Management: Landowners and property managers can employ this model to streamline the process of identifying and eradicating weeds like Waterhemp, reducing labor costs and improving the health and appearance of their green spaces.
Weed Identification Mobile App: A mobile app can be developed using this computer vision model to assist gardeners, farmers, and horticulture enthusiasts in identifying weeds like Waterhemp quickly and accurately, enabling them to make informed decisions about weed management techniques.
Botanical Research: The computer vision model can aid in data collection and analysis for researchers studying the ecology and morphology of various weed species like Waterhemp, expediting the process of understanding and documenting these plants for both scientific and practical purposes.

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{
                            computer-vision-4svyf_dataset,
                            title = { Computer Vision Dataset },
                            type = { Open Source Dataset },
                            author = { Precision Drone Spray },
                            howpublished = { \url{ https://universe.roboflow.com/precision-drone-spray/computer-vision-4svyf } },
                            url = { https://universe.roboflow.com/precision-drone-spray/computer-vision-4svyf },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-04-29 },
                            }