Real-time reef fishes identification using deep learning

Abstract

Reef fishes is an important part in maintaining the balance of various components in the coral reef ecosystem. The existence of reef fish on coral reef ecosystems is a marker of the ecosystem in good condition. Furthermore, it is important to observe the condition of reef fish in a coral reef ecosystem to determine the population and diversity of reef fish in the ecosystem. Observation of reef fish generally by performing a manual visual census by scuba diver. In entering the industrial revolution 4.0 era there is a need to develop technology that is used to monitor the condition of reef fish in a coral reef ecosystem. The development of technology will certainly help researchers, and later on ecosystem manager, in observing the condition of reef fish with automatic identification. The technological development that can be done to observe reef fish is by applying deep learning. In this research we used YOLO deep learning algorithm for automatic identification. YOLO has the advantage of faster object detection. Application of deep learning to identify fish automatically is illustrated using underwater video recording of reef fish.