BUILDING A MODEL FOR COUNTING BREEDING EELS USING YOLOv8

Abstract

The aquaculture ecosystem in Mekong Delta River is a big system that is providing many resources for farmers who is building the breeding eels growing system. It proved that many people can fund much profit when enlarging a good system with a suitable solution for feeding and controlling breeding eels living condition. When the need of a genuine system of counting eels in nowadays is becoming necessary. Some solution that is requested for counting eels and it became that is Deep Learning is a comfortable field for counting eels. With the application of using Deep Learning in enlargement and enhancement in aquaculture system. YOLOv8 can be used to control the system of feeding and controlling eels in Mekong Delta area. The camera for preparing the dataset of breeding eels guide us to build a system of training the breeding eels images with guidance of our advisor. In this work, we propose using YOLO – a real time object algorithm for detecting some eels by picture. We have experimented on dataset which contains about 1241 images of eels. Finally, we integrate the trained model into web application to apply model for solving counting breeding eels problem.