plc_CV Object Detection Dataset and Pre-Trained Model by Yusuf Bayrak

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Explore Dataset

Here are a few use cases for this project:

Security Surveillance System: The "plc_CV" model can be implemented in security and surveillance systems to promptly detect the presence of police or other personnel related to plc classes. This could initiate alerts and help in managing crowd control or incident response processes more effectively.
Smart Traffic Management: This model could be utilized as part of a smart traffic management system, identifying police escorts or patrols and offering priority to their routes, reducing traffic badgering and ensuring public safety.
Media Analysis Software: In journalism and news agencies, this model could analyze video content to identify when police or relevant authorities appear, saving significant time during content categorization or the report development process.
Emergency Response Systems: The model can be integrated into emergency response systems. When a distress signal is activated, the system could utilize camera feeds to identify if the police or necessary authorities have arrived, providing vital real-time updates to operators.
Forensic Investigations: The "plc_CV" can be used to support forensic investigations, analyzing hours of video footage to identify when and where police or other officials appear. This could potentially provide key insights in various investigative scenarios.

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{
                            plc_cv_dataset,
                            title = { plc_CV Dataset },
                            type = { Open Source Dataset },
                            author = { Yusuf Bayrak },
                            howpublished = { \url{ https://universe.roboflow.com/yusuf-bayrak-ude9b/plc_cv } },
                            url = { https://universe.roboflow.com/yusuf-bayrak-ude9b/plc_cv },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-05-06 },
                            }