Shen Furao

Computer Vision and Pattern Recognition · 2006–2022

A researcher in the Science corpus: 9 papers; trusts 169 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 59 citations into it; #12,598 of 21,575 by trust here, #17,258 by citations
• Artificial Intelligence — 48 citations into it; #13,946 of 35,345 by trust here, #17,412 by citations
• Model Architectures — 21 citations into it
• Optimization & Training — 14 citations into it
• Representation & Self-Supervised Learning — 14 citations into it
• Information Systems — 11 citations into it
• Statistical Learning Theory — 11 citations into it
• Generative Models — 10 citations into it; #1,620 of 1,956 by trust here, #1,902 by citations

Whom Shen Furao trusts overall

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

1. Geoffrey E. Hinton
2. Bernd Fritzke
3. Yoshua Bengio
4. Nicolas Le Roux
5. Alex Krizhevsky
6. Teuvo Kohonen
7. Simon Osindero
8. Kaiming He
9. Yann LeCun
10. William W. Hager

Who trusts Shen Furao overall

1. Nicolas P. Rougier
2. Omer Berat Sezer
3. Joonhyuck Lee
4. Aleksandra Dedinec
5. Yann Boniface
6. Kuilin Chen
7. Hua Shen
8. Ren Zhang
9. Dong-Sik Jang
10. M. Ugur Gudelek

Papers from Shen Furao's perspective

Ordered by how strongly the researchers Shen Furao 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. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Forecasting exchange rate using deep belief networks and conjugate gradient method (2015) — 233 citations
• A model with Fuzzy Granulation and Deep Belief Networks for exchange rate forecasting (2014) — 42 citations
• Image Data Augmentation for Deep Learning: A Survey (2022) — 404 citations
• Robust log-based anomaly detection on unstable log data (2019) — 766 citations
• Label Mapping Neural Networks with Response Consolidation for Class Incremental Learning (2019)
• An incremental learning vector quantization algorithm for pattern classification (2012) — 49 citations
• Forecasting exchange rate with deep belief networks (2011) — 47 citations
• Non-I.I.D. Multi-Instance Dimensionality Reduction by Learning a Maximum Bag Margin Subspace (2010) — 16 citations
• An incremental network for on-line unsupervised classification and topology learning (2006) — 334 citations