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Ocean Exploration Models

This repository contains models designed to facilitate ocean exploration, focusing on the identification of various fish species and the detection of ocean trash. These models are intended to contribute to environmental monitoring and conservation efforts, aiding researchers and environmentalists in better understanding and preserving marine ecosystems.

Marine life ID Model

The Marine life Identification Model is trained to recognize and classify various species of marine life commonly found in oceanic environments. It leverages state-of-the-art deep learning techniques to accurately categorize different species based on their visual features.

Ocean Trash Detection Model

The Ocean Trash Detection Model is designed to detect and identify different types of trash and pollutants present in marine ecosystems. It employs advanced image recognition algorithms to locate and categorize various forms of ocean debris, helping to assess the environmental impact and promote cleaner seas.

Use Cases

  • Ecosystem Monitoring: Track the population and distribution of different fish species to assess the health of ocean ecosystems.
  • Pollution Management: Detect and categorize various types of ocean trash to facilitate effective pollution management strategies.
  • Conservation Efforts: Support conservation initiatives by providing insights into the impact of human activities on marine life and habitats.
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Datasets used to train lewiskimaru/Seamore