The goal of the study was to use deep learning to identify yellowfin tuna, mackerel tuna, and skipjack tuna. The researchers used a model called YOLOv5 and found that training the model for 400 epochs resulted in high accuracy. The model achieved a precision of 98.1%, recall of 93.9%, and an overall accuracy of 95% in identifying the three tuna species. This method can help accurately distinguish between these important fish species, which can be valuable for fisheries management and traceability.