124 citations · 301 across the 19 of their papers we have counts for
15 papers · 1 filter
Wavelet-Assisted Mamba for Satellite-Derived Sea Surface Temperature Super-Resolution
Wankun Chen, Feng Gao, Yanhai Gan +3
Sea surface temperature (SST) is an essential indicator of global climate change and one of the most intuitive factors reflecting ocean conditions. Obtaining high-resolution SST da…
Dynamic Frequency Feature Fusion Network for Multi-Source Remote Sensing Data Classification
Yikang Zhao, Feng Gao, Xuepeng Jin +2
Multi-source data classification is a critical yet challenging task for remote sensing image interpretation. Existing methods lack adaptability to diverse land cover types when mod…
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…
Adaptive Frequency Enhancement Network for Remote Sensing Image Semantic Segmentation
Feng Gao, Miao Fu, Jingchao Cao +2
Semantic segmentation of high-resolution remote sensing images plays a crucial role in land-use monitoring and urban planning. Recent remarkable progress in deep learning-based met…
Frequency-Compensated Network for Daily Arctic Sea Ice Concentration Prediction
Jialiang Zhang, Feng Gao, Yanhai Gan +2
Accurately forecasting sea ice concentration (SIC) in the Arctic is critical to global ecosystem health and navigation safety. However, current methods still is confronted with two…
Dynamic Cross-Modal Feature Interaction Network for Hyperspectral and LiDAR Data Classification
Junyan Lin, Feng Gap, Lin Qi +3
Hyperspectral image (HSI) and LiDAR data joint classification is a challenging task. Existing multi-source remote sensing data classification methods often rely on human-designed f…
Global and Local Attention-Based Transformer for Hyperspectral Image Change Detection
Ziyi Wang, Feng Gao, Junyu Dong +1
Recently Transformer-based hyperspectral image (HSI) change detection methods have shown remarkable performance. Nevertheless, existing attention mechanisms in Transformers have li…
MSFMamba: Multi-Scale Feature Fusion State Space Model for Multi-Source Remote Sensing Image Classification
Feng Gao, Xuepeng Jin, Xiaowei Zhou +2
In the field of multi-source remote sensing image classification, remarkable progress has been made by using Convolutional Neural Network (CNN) and Transformer. Recently, Mamba-bas…
Hybrid Convolutional and Attention Network for Hyperspectral Image Denoising
Shuai Hu, Feng Gao, Xiaowei Zhou +2
Hyperspectral image (HSI) denoising is critical for the effective analysis and interpretation of hyperspectral data. However, simultaneously modeling global and local features is r…
SS-MAE: Spatial-Spectral Masked Auto-Encoder for Multi-Source Remote Sensing Image Classification
Junyan Lin, Feng Gao, Xiaocheng Shi +2
Masked image modeling (MIM) is a highly popular and effective self-supervised learning method for image understanding. Existing MIM-based methods mostly focus on spatial feature mo…
Convolution and Attention Mixer for Synthetic Aperture Radar Image Change Detection
Haopeng Zhang, Zijing Lin, Feng Gao +3
Synthetic aperture radar (SAR) image change detection is a critical task and has received increasing attentions in the remote sensing community. However, existing SAR change detect…
Multi-scale Adaptive Fusion Network for Hyperspectral Image Denoising
Haodong Pan, Feng Gao, Junyu Dong +1
Removing the noise and improving the visual quality of hyperspectral images (HSIs) is challenging in academia and industry. Great efforts have been made to leverage local, global o…
Nearest Neighbor-Based Contrastive Learning for Hyperspectral and LiDAR Data Classification
Meng Wang, Feng Gao, Junyu Dong +2
The joint hyperspectral image (HSI) and LiDAR data classification aims to interpret ground objects at more detailed and precise level. Although deep learning methods have shown rem…
Synthetic Aperture Radar Image Change Detection via Layer Attention-Based Noise-Tolerant Network
Desen Meng, Feng Gao, Junyu Dong +2
Recently, change detection methods for synthetic aperture radar (SAR) images based on convolutional neural networks (CNN) have gained increasing research attention. However, existi…
Change Detection from Synthetic Aperture Radar Images via Dual Path Denoising Network
Junjie Wang, Feng Gao, Junyu Dong +2
Benefited from the rapid and sustainable development of synthetic aperture radar (SAR) sensors, change detection from SAR images has received increasing attentions over the past fe…