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How to Use TensorFlow and Cleanvision to Detect Starfish Threats in the Great Barrier Reefby@aravindputrevu
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How to Use TensorFlow and Cleanvision to Detect Starfish Threats in the Great Barrier Reef

by Aravind PutrevuJanuary 25th, 2024
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The blog outlines an innovative approach to protect Australia's Great Barrier Reef using AI and machine learning. It describes the threat posed by crown-of-thorns starfish (COTS) to the reef and how traditional Manta Tow surveys are limited in efficiency and scale. The Great Barrier Reef Foundation, in partnership with CSIRO and Google, initiated a program to use underwater cameras and AI for more effective COTS detection. The technology leverages TensorFlow, CleanVision, KerasCV, and YOLOv8 to identify starfish in underwater videos. CleanVision is used to clean image data for machine learning, ensuring high-quality inputs. The process includes downloading a Kaggle dataset, preparing and augmenting the data, and visualizing bounding boxes. The model, based on YOLOv8, is trained to detect COTS accurately. This AI-powered approach exemplifies the union of technology and ecology for sustainable conservation, highlighting the potential of AI in environmental protection, especially in complex habitats like the Great Barrier Reef.
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Aravind Putrevu

Aravind Putrevu

@aravindputrevu

All things Developers and Data

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Aravind Putrevu@aravindputrevu
All things Developers and Data

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