Zero-Shot Land Cover Classification of SAR-like Imagery using Vision-Language Models

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Authors: A Arivoli, Ashik Sharon M, Mannadithya
Cited by: 0

Abstract

This capsule contains the reproducibility code for the IEEE GRSL submission "Zero-Shot Land Cover Classification of SAR-like Imagery using Vision-Language Models". It implements a comprehensive zero-shot classification framework using CLIP on the EuroSAT dataset. The code includes pipelines for: (1) converting optical imagery to SAR-like intensity, (2) evaluating 10+ prompt engineering strategies strategies (comparing spatial vs. domain-specific prompts), and (3) performing hierarchical classification (Coarse vs. Fine).

Fields of Study & Subjects

Remote-Sensing Image Classification Domain Adaptation and Few-Shot Learning Advanced Neural Network Applications

Publication details

Journal / source
Code Ocean
Publication date
1 January 2026
Language
EN