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Rising Stars
2025

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Rising Stars

D-Index
60
Citations
14399
World Ranking
159
National Ranking
52

Computer Science

D-Index
68
Citations
21706
World Ranking
2061
National Ranking
285

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Danfeng Hong is affiliated with the Chinese Academy of Sciences in China. Their research primarily focuses on the intersection of engineering and computer science, with a significant emphasis on media technology and computer vision and pattern recognition. They actively contribute to advancements in the fields of atmospheric science, ecology, and artificial intelligence as well.

The scientist's work covers a range of topics central to remote sensing and image analysis. These include:

  • Remote-Sensing Image Classification
  • Advanced Image Fusion Techniques
  • Remote Sensing and Land Use
  • Advanced Image and Video Retrieval Techniques
  • Remote Sensing in Agriculture
  • Image and Signal Denoising Methods
  • Image Retrieval and Classification Techniques

Danfeng Hong has published extensively, with notable frequent venues including:

  • IEEE Transactions on Geoscience and Remote Sensing
  • arXiv (Cornell University)
  • IEEE Geoscience and Remote Sensing Letters
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • ISPRS Journal of Photogrammetry and Remote Sensing

Their recent papers demonstrate a focus on hyperspectral image classification, multimodal deep learning for remote-sensing imagery, and advanced model architectures incorporating transformers. Key publications include:

  • Graph Convolutional Networks for Hyperspectral Image Classification, 2020, IEEE Transactions on Geoscience and Remote Sensing
  • More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification, 2020, IEEE Transactions on Geoscience and Remote Sensing
  • SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers, 2021, arXiv (Cornell University)
  • SpectralGPT: Spectral Remote Sensing Foundation Model, 2024, IEEE Transactions on Pattern Analysis and Machine Intelligence

Danfeng Hong collaborates frequently with several researchers, indicating stable research partnerships. Their main co-authors include Jocelyn Chanussot, Bing Zhang, Jing Yao, Lianru Gao, and Naoto Yokoya.

Best Publications

  • Graph Convolutional Networks for Hyperspectral Image Classification

    Danfeng Hong;Lianru Gao;Jing Yao;Bing Zhang

  • Graph Convolutional Networks for Hyperspectral Image Classification

    Danfeng Hong;Lianru Gao;Jing Yao;Bing Zhang

  • More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification

    Danfeng Hong;Lianru Gao;Naoto Yokoya;Jing Yao

  • SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers

    Danfeng Hong;Zhu Han;Jing Yao;Lianru Gao

  • More Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification

    Danfeng Hong;Lianru Gao;Naoto Yokoya;Jing Yao

  • Cascaded Recurrent Neural Networks for Hyperspectral Image Classification

    Renlong Hang;Qingshan Liu;Danfeng Hong;Pedram Ghamisi

  • An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing

    Danfeng Hong;Naoto Yokoya;Jocelyn Chanussot;Xiao Xiang Zhu

  • UIU-Net: U-Net in U-Net for Infrared Small Object Detection

    Unknown

  • SpectralGPT: Spectral Remote Sensing Foundation Model

    Unknown

  • Feature Extraction for Hyperspectral Imagery: The Evolution From Shallow to Deep: Overview and Toolbox

    Behnood Rasti;Danfeng Hong;Renlong Hang;Pedram Ghamisi

  • Deep learning in multimodal remote sensing data fusion: A comprehensive review

    Unknown

  • Multimodal Fusion Transformer for Remote Sensing Image Classification

    Unknown

  • Hyperspectral Image Classification—Traditional to Deep Models: A Survey for Future Prospects

    Unknown

  • Cross-city matters: A multimodal remote sensing benchmark dataset for cross-city semantic segmentation using high-resolution domain adaptation networks

    Unknown

  • Progress and Challenges in Intelligent Remote Sensing Satellite Systems

    Unknown

  • Classification of Hyperspectral and LiDAR Data Using Coupled CNNs

    Renlong Hang;Zhu Li;Pedram Ghamisi;Danfeng Hong

  • Convolutional Neural Networks for Multimodal Remote Sensing Data Classification

    Xin Wu;Danfeng Hong;Jocelyn Chanussot

  • Extended Vision Transformer (ExViT) for Land Use and Land Cover Classification: A Multimodal Deep Learning Framework

    Unknown

  • Classification of Hyperspectral and LiDAR Data Using Coupled CNNs

    Renlong Hang;Zhu Li;Pedram Ghamisi;Danfeng Hong

  • ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features

    Xin Wu;Danfeng Hong;Jiaojiao Tian;Jocelyn Chanussot

  • Multi-feature fusion: Graph neural network and CNN combining for hyperspectral image classification

    Unknown

  • Deep Learning for UAV-based Object Detection and Tracking: A Survey

    Xin Wu;Wei Li;Danfeng Hong;Ran Tao

  • Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification

    Danfeng Hong;Xin Wu;Pedram Ghamisi;Jocelyn Chanussot

  • Multimodal remote sensing benchmark datasets for land cover classification with a shared and specific feature learning model.

    Danfeng Hong;Jingliang Hu;Jing Yao;Jocelyn Chanussot;Jocelyn Chanussot

  • LRR-Net: An Interpretable Deep Unfolding Network for Hyperspectral Anomaly Detection

    Unknown

  • Learnable manifold alignment (LeMA): A semi-supervised cross-modality learning framework for land cover and land use classification

    Danfeng Hong;Naoto Yokoya;Nan Ge;Jocelyn Chanussot

  • FCCDN: Feature Constraint Network for VHR Image Change Detection

    Unknown

  • X-ModalNet: A semi-supervised deep cross-modal network for classification of remote sensing data

    Danfeng Hong;Danfeng Hong;Naoto Yokoya;Gui-Song Xia;Jocelyn Chanussot;Jocelyn Chanussot

  • CoSpace: Common Subspace Learning From Hyperspectral-Multispectral Correspondences

    Danfeng Hong;Naoto Yokoya;Jocelyn Chanussot;Xiao Xiang Zhu

  • Deep Encoder-Decoder Networks for Classification of Hyperspectral and LiDAR Data

    Danfeng Hong;Lianru Gao;Renlong Hang;Bing Zhang

  • Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral Unmixing.

    Danfeng Hong;Lianru Gao;Jing Yao;Naoto Yokoya

  • Interpretable Hyperspectral Artificial Intelligence: When nonconvex modeling meets hyperspectral remote sensing

    Danfeng Hong;Wei He;Naoto Yokoya;Jing Yao

  • Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification

    Danfeng Hong;Xin Wu;Pedram Ghamisi;Jocelyn Chanussot

  • StfNet : A Two-Stream Convolutional Neural Network for Spatiotemporal Image Fusion

    Xun Liu;Chenwei Deng;Jocelyn Chanussot;Danfeng Hong

  • A novel hierarchical approach for multispectral palmprint recognition

    Danfeng Hong;Wanquan Liu;Jian Su;Zhenkuan Pan

Frequent Co-Authors

Jocelyn Chanussot
Jocelyn Chanussot Grenoble Alpes University
Xiao Xiang Zhu
Xiao Xiang Zhu Technical University of Munich
Naoto Yokoya
Naoto Yokoya University of Tokyo
Lianru Gao
Lianru Gao Aerospace Information Research Institute
Bing Zhang
Bing Zhang Chinese Academy of Sciences
Pedram Ghamisi
Pedram Ghamisi Helmholtz-Zentrum Dresden-Rossendorf
Ran Tao
Ran Tao Beijing Institute of Technology
Antonio Plaza
Antonio Plaza University of Extremadura
Qian Du
Qian Du Mississippi State University
Qingshan Liu
Qingshan Liu Nanjing University of Information Science and Technology

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