Diatoms Dataset Object Detection Dataset and Pre-Trained Model by Diatoms Dataset

Images

5904 images

Explore Dataset

Here are a few use cases for this project:

Aquatic Health Monitoring: This model can be used in environmental science to monitor the health of aquatic ecosystems. Because Diatoms are sensitive to changes in water quality, their presence, absence, or proportions can provide valuable information about the health and pollution levels of bodies.
Microbiology Educational Aid: The dataset could be used to create an educational tool that helps students in microbiology courses learn and identify different types of diatoms.
Food Chain Studies: Use the model to identify the concentration and types of diatoms in specific regions. This data can lead to further understanding of the food chain, as diatoms are the primary food source for many marine and freshwater organisms.
Pharmaceutical Research: Some diatom species produce toxins that can be harmful or beneficial. By identifying these species, the model can be used for research in drug discovery and toxicity studies.
Forensic Applications: The presence of certain diatoms in tissues of an organism can indicate drowning as the cause of death. This model could thus be beneficial for forensic investigations.

It's important to clarify that if an example image in the dataset is a close-up of a snake, it may be listed inaccurately. Since the dataset is designed for classification of different types of diatoms (microscopic algae), all images should be relevant to these microscopic species.

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{
                            diatoms-dataset_dataset,
                            title = { Diatoms Dataset Dataset },
                            type = { Open Source Dataset },
                            author = { Diatoms Dataset },
                            howpublished = { \url{ https://universe.roboflow.com/diatoms-dataset/diatoms-dataset } },
                            url = { https://universe.roboflow.com/diatoms-dataset/diatoms-dataset },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-04-20 },
                            }