Masked Armed Bandits Object Detection Dataset and Pre-Trained Model by finalyearproject

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Explore Dataset

Here are a few use cases for this project:

Law Enforcement and Surveillance: Using this computer vision model, law enforcement agencies could better monitor surveillance footage to detect potential threats in real time. The system could flag suspicious behavior, like a masked person carrying a weapon, accelerating response times and potentially saving lives.
Video Analysis: This model could be used for video analysis, allowing security companies to swiftly identify initiating instances of crime in a recorded footage helping to deliver evidence more efficiently in crime investigations.
Public Safety Monitoring: The model could be used in public spaces like parks, malls, sports events, or concerts to detect masked armed bandits, effectively alerting security personnel to potential threats and ensuring public safety.
Social Media Moderation: This model can be beneficial for online platforms, identifying and flagging violent content or images that violate community standards by showing masked individuals with forbidden items.
Video Game Development: In video game designs involving crime solving or adventure elements, this model can allow for more interactive and immersive experiences by recognizing in-game elements like masked bandits with various weapons.

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.

YOLOv5

This project has a YOLOv5 model checkpoint available for inference with Roboflow Deploy. YOLOv5 is a proven and tested, production ready, 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{
                            masked-armed-bandits_dataset,
                            title = { Masked Armed Bandits  Dataset },
                            type = { Open Source Dataset },
                            author = { finalyearproject },
                            howpublished = { \url{ https://universe.roboflow.com/finalyearproject-axe8j/masked-armed-bandits } },
                            url = { https://universe.roboflow.com/finalyearproject-axe8j/masked-armed-bandits },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-04-29 },
                            }