Deep learning dataset Object Detection Dataset and Pre-Trained Model by AUT2023

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Explore Dataset

Here are a few use cases for this project:

Maritime Traffic Management: The model can help maritime authorities to monitor and manage waterway traffic in ports or specific water bodies by identifying the presence and type of sailboat.
Recreational Boating Apps: Developers could use the sailboat identifying feature within recreational boating applications to provide users with real-time information about the type of boats in a certain area or provide sailing recommendations based on their preference.
Marine Rescue Services: The model can be utilized in coastguard or marine rescue operations to quickly identify the type of distressed sailboat, enabling more efficient rescue planning and possibly saving lives.
Leisure and Tourism: The model can be used in applications that provide interactive tours or experiences for tourists at popular waterfront cities or coastal areas, giving them detailed insights about different types of sailboats seen on the skyline.
Research and Education: This model could assist researchers in marine studies to identify and track sailboat classes for various research projects. Additionally, it can be used in educational settings for teaching students about different types of sailboats.

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{
                            deep-learning-dataset_dataset,
                            title = { Deep learning dataset Dataset },
                            type = { Open Source Dataset },
                            author = { AUT2023 },
                            howpublished = { \url{ https://universe.roboflow.com/aut2023/deep-learning-dataset } },
                            url = { https://universe.roboflow.com/aut2023/deep-learning-dataset },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-05-14 },
                            }