Classification of Whale Call Signals Based on the Improved YOLOv5 Model

Underwater target classification is an important research topic in the field of underwater acoustic signal processing, and the classification of marine mammal vocalizations is of great significance for the conservation of them. In this paper, the calls of humpback whales, short-finned pilot whales and sperm whales are taken as the research objects and plotted as spectrograms. Aiming to address the issue of small targets in spectrograms, we proposed an improved model based on YOLOv5 and integrate the Vision Transformer BiFormer module to enhance the detection accuracy of each sample. The test result shows that the mean average precision of all categories in the improved model is 88.1%, a 4.9% increase compared to the pre-improvement performance.