Efficient Prompt Tuning of Large Vision-Language Model for Fine-Grained
Ship Classification
Efficient Prompt Tuning of Large Vision-Language Model for Fine-Grained
Ship Classification
Fine-grained ship classification in remote sensing (RS-FGSC) poses a significant challenge due to the high similarity between classes and the limited availability of labeled data, limiting the effectiveness of traditional supervised classification methods. Recent advancements in large pre-trained Vision-Language Models (VLMs) have demonstrated impressive capabilities in few-shot or zero-shot learning, …