Rong Qu

Computer Vision and Pattern Recognition · 2007–2019

A researcher in the Science corpus: 4 papers; trusts 478 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 197 citations into it
• Artificial Intelligence — 78 citations into it
• Industrial and Manufacturing Engineering — 16 citations into it; #2,212 of 2,521 by trust here, #2,150 by citations
• Management Science and Operations Research — 13 citations into it; #10,915 of 11,946 by trust here, #9,931 by citations
• Model Architectures — 13 citations into it
• Computer Networks and Communications — 12 citations into it

Whom Rong Qu trusts overall

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

1. Edmund Kieran Burke
2. Ross B. Girshick
3. Kaiming He
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Karen Simonyan
7. Shaoqing Ren
8. Yann LeCun
9. Andrew Zisserman
10. Christian Szegedy

Who trusts Rong Qu overall

1. Rhyd Lewis

Papers from Rong Qu's perspective

Ordered by how strongly the researchers Rong Qu 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
4. ImageNet Large Scale Visual Recognition Challenge
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Attention is All you Need (Neural Information Processing Systems)
10. Long Short-Term Memory

Their papers

• A graph-based hyper-heuristic for educational timetabling problems (2007) — 567 citations
• A Survey of Deep Learning-Based Object Detection (2019) — 1,141 citations
• Hyper-heuristics: a survey of the state of the art (2013)
• A survey of search methodologies and automated system development for examination timetabling (2009) — 428 citations