Environmentally relevant foraminifera detection

Object Detection

Environmentally relevant foraminifera detection Computer Vision Project

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Classes (60)
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Adercotryma glomerata
Ammodiscus sp.
Ammonia sp.
Ammoscalaria pseudospiralis
Bolivina pseudopunctata
Brizallina skagerrakensis
Bulimina marginata
Cassidulina laevigata
Cassidulna neoteretis
Cibicides lobatulus
Cornuspira foliacea
Cribrostomoides jeffreysii
Cribrostomoides sp.
Eggerelloides medius
Eggerelloides scaber
Elphidium albiumbilicatum
Elphidium excavatum
Elphidium incertum
Elphidium macellum
Elphidium magellanicum
Elphidium williamsoni
Epistominella exigua
Epistominella vitrea
Glandulina laevigata
Globobulimina sp.
Guttulina lactea
Haplophragmoides bradyi
Hippocrepinella acuta
Hormosinella gracilis
Hyalinea balthica
IOL
Lagena laevis
Lagena mollis
Lagena striata
Leptohalysis catella
Liebusella goesi
Mellonis barleeanum
Milliammina fusca
Milliolinella subrotunda
Nonionella iridea
Nonionella sp. T1
Nonionella turgida
Nonionellina labradorica
Oolina hexagona
Psammosphaera bowmanni
Pullenia osloensis
Pyrgo williamsoni
Quinqueloculina seminula
Quinqueloculina stalkeri
Recurvoides trochamminiforme
Reophax sp.
Spiroplectammina biformis
Stainforthia fusiformis
Textularia bocki
Textularia earlandi
Trifarina angulosa
Trochammina rotaliformis
Trochammina sp.
Uvigerina peregrina

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Description

Here are a few use cases for this project:

  1. Marine ecosystem monitoring: Use the model to monitor and examine Foraminifera populations in different marine environments to assess the health of ecosystems and track changes over time.

  2. Climate change research: Analyze the distribution and abundance of these environmentally relevant foraminifera species in sediment samples to study past and present climate conditions and better understand climate change and its effects on marine life.

  3. Palaeoceanographic studies: Utilize the model to identify foraminifera species in sediment core samples, enabling researchers to reconstruct past oceanic conditions and study changes in paleoceanographic settings.

  4. Environmental impact assessments: Use the model to identify foraminifera species in various geographic locations, aiding in the assessment of environmental impacts due to pollution, infrastructure development, or other anthropogenic factors.

  5. Biodiversity and conservation: Apply the model to detect and study specific foraminifera species in different marine habitats, supporting research on marine biodiversity and aiding in the development of conservation strategies for vulnerable ecosystems.

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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{
                            environmentally-relevant-foraminifera-detection_dataset,
                            title = { Environmentally relevant foraminifera detection Dataset },
                            type = { Open Source Dataset },
                            author = { University of Gothenburg Environmental Science },
                            howpublished = { \url{ https://universe.roboflow.com/university-of-gothenburg-environmental-science/environmentally-relevant-foraminifera-detection } },
                            url = { https://universe.roboflow.com/university-of-gothenburg-environmental-science/environmentally-relevant-foraminifera-detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-12-25 },
                            }