6 papers · 1 filter
Cross-Layer Refinement and Frequency-aware Fusion Network for Multi-Source Remote Sensing Image Classification
Wenhan Xiao, Chuanzheng Gong, Feng Gao +2
Multi-source remote sensing image classification benefits from complementary spectral and structural information. However, identifying discriminative cross-modal features remains c…
Shared-Pattern Collaborative Network for Multi-Source Remote Sensing Data Classification
Chenfang Yang, Chuanzheng Gong, Feng Gao +2
Multi-source remote sensing data classification has received growing attention recently. However, existing methods still struggle to jointly model long-range contextual dependencie…
Semantic-Guided Fusion Network for Multi-Source Remote Sensing Image Classification
Yuwei Zhao, Chuanzheng Gong, Baogui Huan +3
Multi-source remote sensing image classification has attracted increasing attention due to the complementary spectral, structural, and geometric information. However, existing meth…
Dual-Branch State-Displacement Network for Sea Surface Temperature Super-Resolution
Wankun Chen, Feng Gao, Yanhai Gan +4
Sea surface temperature (SST) is a critical indicator of global climate change, yet satellite-derived SST imagery often suffers from coarse spatial resolution, limiting the ability…
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…
Prototype-Based Information Compensation Network for Multi-Source Remote Sensing Data Classification
Feng Gao, Sheng Liu, Chuanzheng Gong +4
Multi-source remote sensing data joint classification aims to provide accuracy and reliability of land cover classification by leveraging the complementary information from multipl…