GRD: An Ultra-Lightweight SAR Ship Detector Based on Global Relationship Distillation
Yue Zhou, Xue Jiang, Lin Chen, Xingzhao Liu · IEEE Geoscience and Remote Sensing Letters · 2023
Most existing works on lightweight SAR ship detectors sacrifice a lot of detection accuracy to reduce model size. In this letter, we propose an ultra-lightweight detector based on distillation technology, which can reduce the parameter quantity of the model while minimizing the damage to the model’s detection accuracy. Due to the scattering interference and speckle noise in SAR images, directly applying the existing ultra-lightweight detectors cannot achieve satisfactory performance for ship detection. As a result, we design a global relationship distillation (GRD) algorithm for the ultra-lightweight SAR ship detector. This algorithm can preserve more global relationships from the teacher and mitigate the accuracy degradation caused by the noise and interference, especially in complex inshore scenarios. Besides, the features learned by this algorithm are robust, and the pruned model is more stable. The superiority of the GRD method over several state-of-the-art distillation methods has been evaluated on the HRSID dataset.