Seami Fish Detection Computer Vision Project

Interntareq

Updated 2 years ago

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Classes (9)
clownfish
cuttlefish
dolphin jellyfish
lionfish
seal
shark
triggerfish
turtle
Description

Here are a few use cases for this project:

  1. Marine Biodiversity Studies: The model can be used by marine biologists and researchers to identify and classify different types of sea creatures in a given location. It can help in understanding the biodiversity of an ecosystem, studying population dynamics, species interactions, and prevalence or decline of certain species.

  2. Aquarium Management: The 'Seami Fish Detection' model could be utilized in large aquariums to identify and monitor the behavior, health, and interactions of various species. For instance, the model can track the location and movement of different species in real-time, facilitating efficient management and care.

  3. Fishing Industry: The model could be applied in the fishing industry to identify and sort fish after a catch, thus improving efficiency and contributing to sustainable fishing practices by minimising bycatch of non-target species like dolphins, turtles or seals.

  4. Underwater Photography and Filmmaking: This model can be implemented in post-production stages of underwater photography and filmmaking to tag and classify different species in their work. This would make it easier for producers to label their content, making it easier to search for specific subjects.

  5. Ecotourism and Dive Operations: The model could be deployed for identifying and providing information about sea creatures to divers and eco-tourists, enriching their undersea experience. This could also enhance safety by identifying potentially dangerous creatures like sharks or lionfish in real-time.

Supervision

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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{
                            seami-fish-detection-2hyc1_dataset,
                            title = { Seami Fish Detection Dataset },
                            type = { Open Source Dataset },
                            author = { Interntareq },
                            howpublished = { \url{ https://universe.roboflow.com/interntareq/seami-fish-detection-2hyc1 } },
                            url = { https://universe.roboflow.com/interntareq/seami-fish-detection-2hyc1 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-09-21 },
                            }