1.7k citations · 4.6k across the 18 of their papers we have counts for
19 papers
SoDa2: Single-Stage Open-Set Domain Adaptation via Decoupled Alignment for Cross-Scene Hyperspectral Image Classification
Yiwen Liu, Minghua Wang, Jing Yao +2
Cross-scene hyperspectral image (HSI) classification stands as a fundamental research topic in remote sensing, with extensive applications spanning various fields. Owing to the inc…
SpectralMamba: Efficient Mamba for Hyperspectral Image Classification
Jing Yao, Danfeng Hong, Chenyu Li +1
Recurrent neural networks and Transformers have recently dominated most applications in hyperspectral (HS) imaging, owing to their capability to capture long-range dependencies fro…
Low-Rank Representations Meets Deep Unfolding: A Generalized and Interpretable Network for Hyperspectral Anomaly Detection
Chenyu Li, Bing Zhang, Danfeng Hong +2
Current hyperspectral anomaly detection (HAD) benchmark datasets suffer from low resolution, simple background, and small size of the detection data. These factors also limit the p…
SpectralGPT: Spectral Remote Sensing Foundation Model
Danfeng Hong, Bing Zhang, Xuyang Li +11
The foundation model has recently garnered significant attention due to its potential to revolutionize the field of visual representation learning in a self-supervised manner. Whil…
Cross-City Matters: A Multimodal Remote Sensing Benchmark Dataset for Cross-City Semantic Segmentation using High-Resolution Domain Adaptation Networks
Danfeng Hong, Bing Zhang, Hao Li +7
Artificial intelligence (AI) approaches nowadays have gained remarkable success in single-modality-dominated remote sensing (RS) applications, especially with an emphasis on indivi…
Tensor Decompositions for Hyperspectral Data Processing in Remote Sensing: A Comprehensive Review
Minghua Wang, Danfeng Hong, Zhu Han +5
Owing to the rapid development of sensor technology, hyperspectral (HS) remote sensing (RS) imaging has provided a significant amount of spatial and spectral information for the ob…
Decoupled-and-Coupled Networks: Self-Supervised Hyperspectral Image Super-Resolution with Subpixel Fusion
Danfeng Hong, Jing Yao, Deyu Meng +2
Enormous efforts have been recently made to super-resolve hyperspectral (HS) images with the aid of high spatial resolution multispectral (MS) images. Most prior works usually perf…
Deep Learning in Multimodal Remote Sensing Data Fusion: A Comprehensive Review
Jiaxin Li, Danfeng Hong, Lianru Gao +4
With the extremely rapid advances in remote sensing (RS) technology, a great quantity of Earth observation (EO) data featuring considerable and complicated heterogeneity is readily…
SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers
Danfeng Hong, Zhu Han, Jing Yao +4
Hyperspectral (HS) images are characterized by approximately contiguous spectral information, enabling the fine identification of materials by capturing subtle spectral discrepanci…
Multimodal Remote Sensing Benchmark Datasets for Land Cover Classification with A Shared and Specific Feature Learning Model
Danfeng Hong, Jingliang Hu, Jing Yao +2
As remote sensing (RS) data obtained from different sensors become available largely and openly, multimodal data processing and analysis techniques have been garnering increasing i…
Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral Unmixing
Danfeng Hong, Lianru Gao, Jing Yao +4
Over the past decades, enormous efforts have been made to improve the performance of linear or nonlinear mixing models for hyperspectral unmixing, yet their ability to simultaneous…
Interpretable Hyperspectral AI: When Non-Convex Modeling meets Hyperspectral Remote Sensing
Danfeng Hong, Wei He, Naoto Yokoya +5
Hyperspectral imaging, also known as image spectrometry, is a landmark technique in geoscience and remote sensing (RS). In the past decade, enormous efforts have been made to proce…
Hyperspectral Image Classification-Traditional to Deep Models: A Survey for Future Prospects
Muhammad Ahmad, Sidrah Shabbir, Swalpa Kumar Roy +7
Hyperspectral Imaging (HSI) has been extensively utilized in many real-life applications because it benefits from the detailed spectral information contained in each pixel. Notably…
PolSAR Image Classification Based on Robust Low-Rank Feature Extraction and Markov Random Field
Haixia Bi, Jing Yao, Zhiqiang Wei +2
Polarimetric synthetic aperture radar (PolSAR) image classification has been investigated vigorously in various remote sensing applications. However, it is still a challenging task…
More Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification
Danfeng Hong, Lianru Gao, Naoto Yokoya +4
Classification and identification of the materials lying over or beneath the Earth's surface have long been a fundamental but challenging research topic in geoscience and remote se…
Graph Convolutional Networks for Hyperspectral Image Classification
Danfeng Hong, Lianru Gao, Jing Yao +3
To read the final version please go to IEEE TGRS on IEEE Xplore. Convolutional neural networks (CNNs) have been attracting increasing attention in hyperspectral (HS) image classifi…
Cross-Attention in Coupled Unmixing Nets for Unsupervised Hyperspectral Super-Resolution
Jing Yao, Danfeng Hong, Jocelyn Chanussot +3
The recent advancement of deep learning techniques has made great progress on hyperspectral image super-resolution (HSI-SR). Yet the development of unsupervised deep networks remai…
Spectral Superresolution of Multispectral Imagery with Joint Sparse and Low-Rank Learning
Lianru Gao, Danfeng Hong, Jing Yao +3
Extensive attention has been widely paid to enhance the spatial resolution of hyperspectral (HS) images with the aid of multispectral (MS) images in remote sensing. However, the ab…
Spatial-Spectral Manifold Embedding of Hyperspectral Data
Danfeng Hong, Jing Yao, Xin Wu +2
In recent years, hyperspectral imaging, also known as imaging spectroscopy, has been paid an increasing interest in geoscience and remote sensing community. Hyperspectral imagery i…