Qifa Ke

Computer Vision and Pattern Recognition · 2005–2018

A researcher in the Science corpus: 6 papers; trusts 765 researchers and is trusted by 731 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 109 citations into it; #1,597 of 21,575 by trust here, #3,476 by citations
• Artificial Intelligence — 49 citations into it; #24,062 of 35,345 by trust here, #16,471 by citations
• Natural Language Processing — 30 citations into it; #2,012 of 5,688 by trust here, #2,473 by citations
• Representation & Self-Supervised Learning — 28 citations into it; #1,333 of 3,145 by trust here, #1,246 by citations
• Information Retrieval & Search — 20 citations into it; #280 of 1,022 by trust here, #462 by citations
• Media Technology — 20 citations into it
• Aerospace Engineering — 15 citations into it
• Evaluation & Benchmarks — 12 citations into it

Whom Qifa Ke trusts overall

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

1. David G. Lowe
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Kaiming He
5. Andrew Zisserman
6. Yoshua Bengio
7. Antonio Torralba
8. Diederik P. Kingma
9. Yann LeCun
10. Herv'e J'egou

Who trusts Qifa Ke overall

1. Nicolas Gillis
2. Shuhang Gu
3. Nojun Kwak
4. Artem Babenko
5. John Wright
6. Shankar R. Rao
7. Anders P. Eriksson
8. Zhao Song
9. Ran He
10. Hanwang Zhang

Papers from Qifa Ke's perspective

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

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

Their papers

• A Multi-View Embedding Space for Modeling Internet Images, Tags, and Their Semantics (2012) — 588 citations
• Optimized Product Quantization for Approximate Nearest Neighbor Search (2013) — 491 citations
• Optimized Product Quantization (2014) — 506 citations
• Bundling features for large scale partial-duplicate web image search (2009) — 451 citations
• Robust L/sub 1/ norm factorization in the presence of outliers and missing data by alternative convex programming (2005) — 693 citations
• Paragraph-level Neural Question Generation with Maxout Pointer and Gated Self-attention Networks (2018) — 278 citations