Official Porifera Classifier Computer Vision Project
Traditional classification methods of marine sponges are labour-intensive and depend on expertise, limiting their scalability, among many other complications. To address these challenges, we developed the “Porifera Classifier”, a deep learning, computer vision model trained on a curated dataset of 16,915 labelled images that allows it to detect and classify up to 126 species of marine sponges. Established through a YOLOv8 architecture, the model ensures state-of-the-art accuracy benchmarks based on the detection of amorphous and highly varying structural objects. It further evaluates the integration of algorithms that compensate for light scattering in underwater recordings. The annotated dataset also serves as a valuable resource for future studies.
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{
official-porifera-classifier-ju8er_dataset,
title = { Official Porifera Classifier Dataset },
type = { Open Source Dataset },
author = { Marine Sciences Research Station },
howpublished = { \url{ https://universe.roboflow.com/marine-sciences-research-station/official-porifera-classifier-ju8er } },
url = { https://universe.roboflow.com/marine-sciences-research-station/official-porifera-classifier-ju8er },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { mar },
note = { visited on 2024-04-28 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the Official Porifera Classifier project in your project.