Intelligence technologies play an important role in increasing product quality and production
efficiency in digital aquaculture. Automatic fish detection will contribute to achieving …

In aquaculture, Behavioral monitoring of fish contributes to scientific management and
reduces the threat of loss from disease and stress. Fish tracking technology plays an …

Video monitoring systems are successfully widely used in many on-land artificial intelligence
applications. They have been introduced into fishery production in recent years, such as …

Due to the influence of underwater visual characteristics on the observation of underwater
creatures, the traditional object detection algorithm is ineffective. In order to improve the …

In marine aquaculture, fish populations constantly decrease throughout the cultivation
period because of mortality and escape. Current production management systems provide …

To detect and identify fish in the wild, there are many challenges mainly due to the distinctive
perception environment in the ocean. Another important issue is the lack of sufficient image …

The task of accurately classifying marine fish species is of great importance to marine
ecosystem investigations, but previously used methods were extremely labor-intensive …

To meet the increasing demand for aquacultural products, it is necessary to increase
cultured fish production and to ensure that the fish species grow with maximum efficiency. A …

A version of the YOLO detection algorithm, the YOLOv4, has yet to find much use on aquatic
species. Detection systems optimized for aquarium fish species are also currently lacking …

A fish can be detected by means of artificial vision techniques, without human intervention or
handling the fish. This work presents an application for detecting moving fish in water by …