rice-field-insect-detection Object Detection Dataset and Pre-Trained Model by Laguna State Polytechnic University SCC

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Explore Dataset

Here are a few use cases for this project:

Pest Early Warning System: By integrating this model into an agricultural monitoring system, farmers can receive early notifications when specific harmful insect populations start to rise, enabling them to take appropriate countermeasures.
Crop Health Analysis: Research institutions can analyze crop health in relation to the presence of different types of insects, which might lead to more effective pest control strategies.
Biodiversity Study: Ecologists can use the model for studying biodiversity in different rice fields, understanding the ecosystem balance therein, and suggesting solutions to maintain or enhance it if required.
Automated Farming: In high-tech farming or agricultural drones, this model can be used to identify and target specific insect pests for treatment, reducing the need for broad-spectrum insecticides and enhancing farm productivity.
Pesticide Efficiency Analysis: Agricultural scientists can use the model pre and post pesticide use to evaluate its efficiency against the targeted insects and to optimize the usage of pesticides in the future based on this data.

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.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

Cite This Project

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

@misc{
                            rice-field-insect-detection_dataset,
                            title = { rice-field-insect-detection Dataset },
                            type = { Open Source Dataset },
                            author = { Laguna State Polytechnic University  SCC },
                            howpublished = { \url{ https://universe.roboflow.com/laguna-state-polytechnic-university-scc/rice-field-insect-detection } },
                            url = { https://universe.roboflow.com/laguna-state-polytechnic-university-scc/rice-field-insect-detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { may },
                            note = { visited on 2024-07-27 },
                            }