The detection of Enteromorpha prolifera stands as a pivotal research area within the realm of intelligent marine environment monitoring. Addressing the challenge posed by the substantial training sample requirements inherent in conventional methods of Enteromorpha prolifera detection, this paper proposes GBS-LD model. By introducing a global context module and background distillation loss branch, the shortcomings of the original position distillation method in modeling background features are solved, effectively improving the robustness of detection system in complex marine environments. Our proposed model has achieved high accuracy and real-time performance in the dataset of Enteromorpha prolifera,providing important reference for intelligent monitoring of marine.
维普
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