7 papers
Frequency and Edge-Guided Segment Anything Model for Remote Sensing Image Semantic Segmentation
Feng Gao, Zizhe Pan, Haoting Wang +4
Remote sensing image semantic segmentation (RSISS) has attracted significant attention due to the growing demand for fine-grained land cover information. The Segment Anything Model…
Axial-Relation Guided Fusion State Space Model for Optical-Elevation Sensing Image Segmentation
Feng Gao, Zhilin Jin, Yanhai Gan +2
Semantic segmentation of multi-source remote sensing images is a fundamental task for Earth observation applications. Existing methods often struggle with insufficient multi-scale…
Synthetic Aperture Radar Image Change Detection Based on Global Dynamic Context-Aware Network
Baogui Huan, Chuanzheng Gong, Dezhong Chen +3
Convolutional neural networks (CNNs) have been extensively and successfully applied to the task of synthetic aperture radar (SAR) image change detection. However, conventional conv…
Spectral Dynamic Attention Network for Hyperspectral Image Super-Resolution
Tengya Zhang, Feng Gao, Lin Qi +2
Hyperspectral image super-resolution is essential for enhancing the spatial fidelity of HSI data, yet existing deep learning methods often struggle with substantial spectral redund…
Representative Spectral Correlation Network for Multi-source Remote Sensing Image Classification
Chuanzheng Gong, Feng Gao, Junyan Lin +2
Hyperspectral image (HSI) and SAR/LiDAR data offer complementary spectral and structural information for land-cover classification. However, their effective fusion remains challeng…
Frequency-Enhanced Hilbert Scanning Mamba for Short-Term Arctic Sea Ice Concentration Prediction
Feng Gao, Zheng Gong, Wenli Liu +4
While Mamba models offer efficient sequence modeling, vanilla versions struggle with temporal correlations and boundary details in Arctic sea ice concentration (SIC) prediction. To…