Face_spoof_detection Object Detection Dataset and Pre-Trained Model by ABINET ALEMU

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Explore Dataset

Here are a few use cases for this project:

Security Systems: The "Face_spoof_detection" model can be used to beef up security in systems relying on face recognition. This could be used in secured facilities, offices, or homes to ensure unauthorized individuals can't gain access using printed photos, masks, or even digital manipulation.
Smartphone Authentication: Mobile device manufacturers might benefit from this model to enhance their facial recognition-based unlocking system. They can use it to detect if someone is trying to unlock a phone using a printed photo or a manipulated digital image, helping to prevent unauthorized access.
ATM and Banking: The banking industry can use this model in ATM machines and bank gateways where face recognition is used. It can help in preventing fraudsters from spoofing face recognition systems to gain illegal access to users' bank accounts.
Surveillance Systems: Law enforcement and security companies could use this model in surveillance cameras. It would allow them to easily detect if someone is attempting to spoof a face, alerting them to potential deceitful activities or intrusions.
Online Examination Systems: This model can be used in online proctoring systems where it's important to ensure the integrity of the exam process. It can add an additional layer of security to verify the real presence of a test-taker and prevent someone from using a fake or manipulated image to take the test on behalf of someone else.

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{
                            face_spoof_detection_dataset,
                            title = { Face_spoof_detection Dataset },
                            type = { Open Source Dataset },
                            author = { ABINET ALEMU },
                            howpublished = { \url{ https://universe.roboflow.com/abinet-alemu-tsand/face_spoof_detection } },
                            url = { https://universe.roboflow.com/abinet-alemu-tsand/face_spoof_detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { feb },
                            note = { visited on 2024-05-13 },
                            }