test sample Object Detection Dataset and Pre-Trained Model by goodtim123@naver.com

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Explore Dataset

Here are a few use cases for this project:

Construction Site Safety: The model can be used to identify and monitor personnel's presence in high-risk areas within a construction zone. This can increase safety by triggering alerts if a person is detected near dangerous machinery such as a crane or a forklift.
Work Efficiency Tracking: The model could be utilized in logistics or manufacturing sectors to monitor the activity of personnel and the usage of machines. It could provide data on workflow and potentially help identify bottlenecks or areas for efficiency improvement.
Surveillance Systems: With the ability to detect persons, the model can be used in surveillance systems to send alerts when someone enters a secure zone.
Occupational Training: This model could also be used for training purposes. It can help in designing modules on how an individual needs to interact with heavy machinery within large areas, keeping their safety in mind.
Autonomous Machinery: In industries integrating autonomous machinery, the model can be used to ensure the autonomous systems recognize and respond appropriately to humans, thus enhancing co-working safety.

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-sample-acrqh_dataset,
                            title = { test sample Dataset },
                            type = { Open Source Dataset },
                            author = { goodtim123@naver.com },
                            howpublished = { \url{ https://universe.roboflow.com/goodtim123-naver-com/test-sample-acrqh } },
                            url = { https://universe.roboflow.com/goodtim123-naver-com/test-sample-acrqh },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { apr },
                            note = { visited on 2024-04-19 },
                            }