An Automatic Detection System for Marine Ranch Biological Targets Based on Deep Learning

Abstract

With the rapid development of deep learning in marine biological testing, its status in marine ecological testing and resource development continues to increase. Among them, marine underwater biological target detection, for marine aquaculture, protection of marine endangered organisms. The development of marine ecological monitoring and other aspects is of great significance. In the application of sea bed base and marine pasture biological quantity statistics, artificial intelligence can also replace traditional methods, making the whole process more efficient and accurate. In this paper, the requirements of the marine ranch for automatic detection of biological targets are technically researched from three aspects: system architecture design, algorithm model, and system realization, to build an automatic detection system for marine ranch biological targets based on deep learning.