Detrimental Starfish Detection on Embedded System: A Case Study of YOLOv5 Deep Learning Algorithm and TensorFlow Lite framework

Detrimental Starfish Detection on Embedded System: A Case Study of YOLOv5 Deep Learning Algorithm and TensorFlow Lite framework

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There is a great range of spectacular coral reefs in the ocean world.Unfortunately, they are in jeopardy, due to an overabundance of one specific starfish called thread feathers cabernet the coral-eating crown-of-thorns starfish (or COTS).This article provides research to deliver innovation in COTS control.

Using a deep learning model based on the You Only Look Once version dodge dart radiator hose 5 (YOLOv5) deep learning algorithm on an embedded device for COTS detection.It aids professionals in optimizing their time, resources and enhancing efficiency for the preservation of coral reefs all around the world.As a result, the performance over the algorithm was outstanding with Precision: 0.

93 - Recall: 0.77 - F1-score: 0.84.