myfyp Computer Vision Project

trainyolov7

Updated 2 years ago

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Description

Here are a few use cases for this project:

  1. Examination Invigilation: The model could be deployed during online or offline examinations to monitor instances of cheating. By identifying non-permissible actions such as looking at a fellow candidate's paper or making suspicious hand gestures, it can help maintain the integrity of the exam.

  2. Online Test Proctoring: Many online courses and certification programs involve exams which need proctoring. "myfyp" could provide an automated proctoring solution, spotting potential cheat attempts without human intervention.

  3. Surveillance in High-Stakes Testing: In high-stakes testing scenarios such as entrance exams or professional qualification tests, the model can be used to ensure fair testing conditions and identify irregular behavior, promoting a level-playing field for all participants.

  4. Prevent Academic Misconduct in Schools/Colleges: This model can help academic institutions monitor students' actions during school exams and identify any improper activity, fostering a culture of academic honesty.

  5. Employee Integrity Checks: In workplaces which involve written tests as part of recruitment or evaluation, the model can help assess the honesty of employees or candidates, potentially highlighting those who may act dishonestly in other areas of their work.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            myfyp-kjkqe_dataset,
                            title = { myfyp Dataset },
                            type = { Open Source Dataset },
                            author = { trainyolov7 },
                            howpublished = { \url{ https://universe.roboflow.com/trainyolov7/myfyp-kjkqe } },
                            url = { https://universe.roboflow.com/trainyolov7/myfyp-kjkqe },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { feb },
                            note = { visited on 2024-11-24 },
                            }