English(EN) DDF2Pol: A Dual-Domain Feature Fusion Network for PolSAR Image Classification

新的 DDF2Pol 网络在 PolSAR 图像分类中实现高精度

作者 PulseAugur 编辑部 · [1 个来源] · 2026-04-20 21:22

研究人员开发了 DDF2Pol，这是一种用于分类 PolSAR 图像的新型双域卷积神经网络。该网络利用并行实值和复值流提取互补信息，并通过深度卷积和坐标注意力机制进行增强。实验表明，DDF2Pol 在基准数据集上实现了高精度，在 Flevoland 上达到 98.16%，在 San Francisco 上达到 96.12%，参数量仅为 91,371。 AI

排序理由这是一篇详细介绍图像分类新模型的学术论文。

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Hugging Face Daily Papers TIER_1 English(EN) · 2026-04-20 21:22

DDF2Pol: 一种用于PolSAR图像分类的双域特征融合网络

This paper presents DDF2Pol, a lightweight dual-domain convolutional neural network for PolSAR image classification. The proposed architecture integrates two parallel feature extraction streams, one real-valued and one complex-valued, designed to capture complementary spatial and…

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DDF2Pol: 一种用于PolSAR图像分类的双域特征融合网络

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