Visual-Semantic Cooperative Learning for Few-Shot SAR Target Classification

Visual-Semantic Cooperative Learning for Few-Shot SAR Target Classification

Nowadays, meta-learning is the mainstream method for solving few-shot synthetic aperture radar (SAR) target classification, devoted to learning a lot of empirical knowledge from the source domain to quickly recognize the novel classes after seeing only a few samples. However, obtaining the source do...

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Bibliographic Details
Main Authors: Siyuan Wang, Yinghua Wang, Xiaoting Zhang, Chen Zhang, Hongwei Liu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Few-shot
semantic
synthetic aperture radar (SAR)
target classification
vision language model (VLM)
Online Access:https://ieeexplore.ieee.org/document/10843851/

Internet

https://ieeexplore.ieee.org/document/10843851/

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