Thesis a_k Object Detection Dataset and Pre-Trained Model by Thesis

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Explore Dataset

Here are a few use cases for this project:

Public Safety and Surveillance: The "Thesis a_k" model could be used in street surveillance systems to detect potential crimes involving knives in real-time, allowing immediate police notification and intervention. The detection of 'victim_hands_up' is particularly useful to identify criminal encounters.
Social Media Monitoring: Social media platforms could use this model to scan and flag content that includes potentially harmful or violent imagery, thereby ensuring safer online spaces and adherence to ethical guidelines.
Crime Scene Investigation Assistance: The model can assist law enforcement agencies by analyzing crime scene photos or videos, enabling faster identification of assailants or understanding the sequence of events.
Forensic Training: The model could serve as a training tool for forensic science students or law enforcement officers, aiding in the identification of assault scenarios involving knives, distinguishing between victims and assailants based on body language.
Video Game Development: Developers creating first-person action or detective games could use this model to create more accurate and immersive environments, where players need to identify potential threats or solve crime mysteries.

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{
                            thesis-a_k_dataset,
                            title = { Thesis a_k Dataset },
                            type = { Open Source Dataset },
                            author = { Thesis },
                            howpublished = { \url{ https://universe.roboflow.com/thesis-jhiiw/thesis-a_k } },
                            url = { https://universe.roboflow.com/thesis-jhiiw/thesis-a_k },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-05-07 },
                            }