Underwater fish detection and counting using image segmentation
Underwater fish detection and counting using image segmentation is a scholarly work, published in 2024 in ''Aquaculture International''. The main subjects of the publication include segmentation, fishery, Actinopterygii, artificial intelligence, image segmentation, computer science, computer vision, subaquaria, water quality, pattern recognition, and DNA barcoding. The study introduces a BoTS-YOLOv5s-seg model based on YOLOv5s to achieve accurate detection of fish edge by using the YOLOv5s instance segmentation model and improving the loss function to SIoU loss while improving non-maximum suppression to reduce missed detection of overlapping objects, and finally incorporating a bottleneck transformer to make the model more focused on valid image information and reduce the model parameters.