Danfeng Hong
Computer Vision and Pattern Recognition · 2017–2023
A researcher in the Science corpus: 17 papers; trusts 480 researchers and is trusted by 25 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 315 citations into it; #7,014 of 21,575 by trust here, #6,371 by citations
- Media Technology — 269 citations into it; #578 of 3,621 by trust here, #324 by citations
- Artificial Intelligence — 158 citations into it; #33,631 of 35,345 by trust here, #15,236 by citations
- Atmospheric Science — 102 citations into it
- Model Architectures — 65 citations into it
- Ecology — 40 citations into it; #3,373 of 10,717 by trust here, #4,893 by citations
- Analytical Chemistry — 37 citations into it
- Aerospace Engineering — 34 citations into it
Whom Danfeng Hong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Ilya Sutskever
- Yann LeCun
- Ross B. Girshick
- Karen Simonyan
- Jimmy Ba
Who trusts Danfeng Hong overall
- Swalpa Kumar Roy
- Jing Yao
- Xin Wu
- Muhammad Ahmad
- Yuan Yuan
- Guangrui Zhao
- Jiazhou Chen
- Yapeng Li
- Bing Zhang
- Jocelyn Chanussot
Papers from Danfeng Hong's perspective
Ordered by how strongly the researchers Danfeng Hong trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Going deeper with convolutions
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- UIU-Net: U-Net in U-Net for Infrared Small Object Detection (2022) — 920 citations
- Extended Vision Transformer (ExViT) for Land Use and Land Cover Classification: A Multimodal Deep Learning Framework (2023) — 328 citations
- Cross-City Matters: A Multimodal Remote Sensing Benchmark Dataset for Cross-City Semantic Segmentation using High-Resolution Domain Adaptation Networks (2023) — 511 citations
- SpectralGPT: Spectral Remote Sensing Foundation Model (2023) — 837 citations
- Convolutional Neural Networks for Multimodal Remote Sensing Data Classification (2022) — 317 citations
- Deep Learning in Multimodal Remote Sensing Data Fusion: A Comprehensive Review (2022) — 692 citations
- Progress and Challenges in Intelligent Remote Sensing Satellite Systems (2022) — 365 citations
- Multimodal Fusion Transformer for Remote Sensing Image Classification (2022) — 500 citations
- Deep Learning for Unmanned Aerial Vehicle-Based Object Detection and Tracking: A survey (2021) — 296 citations
- SpectralFormer: Rethinking Hyperspectral Image Classification With Transformers (2021) — 1,401 citations
- Hyperspectral Image Classification—Traditional to Deep Models: A Survey for Future Prospects (2021) — 366 citations
- Feature Extraction for Hyperspectral Imagery: The Evolution From Shallow to Deep: Overview and Toolbox (2020) — 480 citations
- More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification (2020) — 1,193 citations
- Graph Convolutional Networks for Hyperspectral Image Classification (2020) — 1,248 citations
- Classification of Hyperspectral and LiDAR Data Using Coupled CNNs (2020) — 367 citations
- An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing (2018) — 828 citations
- Cascaded Recurrent Neural Networks for Hyperspectral Image Classification (2017) — 680 citations