Thesis 3.0 Object Detection Dataset and Pre-Trained Model by ISEP

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Explore Dataset

Here are a few use cases for this project:

In-Car Infotainment System Development: "Thesis 3.0" could be implemented in developing new automotive infotainment systems where it can identify and categorize various Android auto icons, simplifying the process and improving system efficiency.
Icon & User Interface Design Testing: The model could be used by UI/UX designers to test and ensure their newly designed icons are recognizable in comparison to existing Android Automotive Icons.
Interactive Tutorial Creation: Developers could use "Thesis 3.0" to design educational or interactive tutorials for new users of automotive software systems, by enabling the model to identify and explain the function of each Android Automotive Icon.
Automotive Software Documentation: The model could be deployed in automating the creation of comprehensive software documentation, by identifying and explaining all the icons used in the interface, thereby improving the overall usability and user experience.
Automated Customer Support: "Thesis 3.0" could be integrated into an AI-driven customer support system, aiding in troubleshooting by recognising the Android Automotive Icons a user might be having issues with, thereby improving customer service response and efficiency.

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-3.0_dataset,
                            title = { Thesis 3.0 Dataset },
                            type = { Open Source Dataset },
                            author = { ISEP },
                            howpublished = { \url{ https://universe.roboflow.com/isep-jvcvx/thesis-3.0 } },
                            url = { https://universe.roboflow.com/isep-jvcvx/thesis-3.0 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-05-07 },
                            }