output
20172026
most citedGraph Convolutional Networks for Hyperspectral Image Classification

1.7k citations

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10 papers · 1 filter

eess.IV2026★ 1 cited

GeoDiff-SAR: A Geometric Prior Guided Diffusion Model for SAR Image Generation

Fan Zhang, Xuanting Wu, Fei Ma +2

Synthetic aperture radar (SAR) image generation can mitigate data scarcity, but controllablegeneration under sparse observation angles remains difficult. Recent SAR generative stud…

eess.IV2025★ 2 cited

Diverse Instance Generation via Diffusion Models for Enhanced Few-Shot Object Detection in Remote Sensing Images

Yanxing Liu, Jiancheng Pan, Jianwei Yang +3

Few-shot object detection (FSOD) aims to detect novel instances with only a limited number of labeled training samples, presenting a challenge that is particularly prominent in num…

eess.IV2024★ 56 cited

Dual-Branch Subpixel-Guided Network for Hyperspectral Image Classification

Zhu Han, Jin Yang, Lianru Gao +3

Deep learning (DL) has been widely applied into hyperspectral image (HSI) classification owing to its promising feature learning and representation capabilities. However, limited b…

eess.IV2023★ 10 cited

Reconstructing Three-decade Global Fine-Grained Nighttime Light Observations by a New Super-Resolution Framework

Jinyu Guo, Feng Zhang, Hang Zhao +2

Satellite-collected nighttime light provides a unique perspective on human activities, including urbanization, population growth, and epidemics. Yet, long-term and fine-grained nig…

eess.IV2022★ 22 cited

Multi-frequency PolSAR Image Fusion Classification Based on Semantic Interactive Information and Topological Structure

Yice Cao, Yan Wu, Ming Li +3

Compared with the rapid development of single-frequency multi-polarization SAR image classification technology, there is less research on the land cover classification of multifreq…

eess.IV2021★ 59 cited

A Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-resolution

Yue Shi, Liangxiu Han, Lianghao Han +3

Realistic hyperspectral image (HSI) super-resolution (SR) techniques aim to generate a high-resolution (HR) HSI with higher spectral and spatial fidelity from its low-resolution (L…