Huan Fu

Computer Vision and Pattern Recognition · 2013–2023

A researcher in the Science corpus: 31 papers; trusts 1,861 researchers and is trusted by 55 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 952 citations into it; #3,695 of 21,575 by trust here, #2,191 by citations
• Artificial Intelligence — 459 citations into it
• Radiology, Nuclear Medicine and Imaging — 261 citations into it
• Model Architectures — 129 citations into it
• Ophthalmology — 121 citations into it
• Evaluation & Benchmarks — 83 citations into it
• Representation & Self-Supervised Learning — 82 citations into it
• Computational Mechanics — 75 citations into it

Whom Huan Fu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Ross B. Girshick
5. Karen Simonyan
6. Diederik P. Kingma
7. Yoshua Bengio
8. Yann LeCun
9. Ilya Sutskever
10. Andrew Zisserman

Who trusts Huan Fu overall

1. Wenguan Wang
2. Deng-Ping Fan
3. Dingwen Zhang
4. Changqing Zhang
5. Jianbing Shen
6. Junwei Han
7. Shariq Farooq Bhat
8. Ibraheem Alhashim
9. Xinzhu Ma
10. Jianlong Wu

Papers from Huan Fu's perspective

Ordered by how strongly the researchers Huan Fu trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Gradient-based learning applied to document recognition
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Deep Ordinal Regression Network for Monocular Depth Estimation (2018) — 2,009 citations
• 3D-FUTURE: 3D Furniture Shape with TextURE (2020) — 417 citations
• PraNet: Parallel Reverse Attention Network for Polyp Segmentation (2020) — 1,833 citations
• Low-Rank Tensor Constrained Multiview Subspace Clustering (2015) — 487 citations
• Cluster-based Co-saliency Detection (2013) — 411 citations
• Diversity-induced Multi-view Subspace Clustering (2015) — 690 citations
• Salient Object Detection in the Deep Learning Era: An In-Depth Survey (2019) — 747 citations
• Depth Enhanced Saliency Detection Method (2014) — 360 citations
• Unsupervised spatially embedded deep representation of spatial transcriptomics (2021) — 403 citations
• Transformers in Medical Imaging: A Survey (2022) — 1,206 citations
• Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST (2023) — 605 citations
• Cross-level Feature Aggregation Network for Polyp Segmentation (2023) — 295 citations
• FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and Correction (2022) — 423 citations
• Alleviating Semantics Distortion in Unsupervised Low-Level Image-to-Image Translation via Structure Consistency Constraint (2022) — 24 citations
• Trusted Multi-View Classification With Dynamic Evidential Fusion (2022) — 474 citations
• Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers (2021) — 571 citations
• Applications of Deep Learning in Fundus Images: A Review (2021) — 338 citations
• Generalized Latent Multi-View Subspace Clustering (2020) — 650 citations
• Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images (2020) — 1,137 citations
• Deep Partial Multi-View Learning (2020) — 315 citations