Zeeshan Hayder

Computer Vision and Pattern Recognition · 2015–2017

A researcher in the Science corpus: 4 papers; trusts 996 researchers and is trusted by 444 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 132 citations into it; #1,990 of 21,575 by trust here, #5,565 by citations
• Artificial Intelligence — 32 citations into it
• Evaluation & Benchmarks — 21 citations into it; #909 of 3,147 by trust here, #1,517 by citations
• Aerospace Engineering — 18 citations into it
• Model Architectures — 8 citations into it
• Media Technology — 7 citations into it

Whom Zeeshan Hayder trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Jifeng Dai
4. Bharath Hariharan
5. Pablo Arbeláez
6. Jitendra Malik
7. Alex Krizhevsky
8. Geoffrey E. Hinton
9. Shaoqing Ren
10. Karen Simonyan

Who trusts Zeeshan Hayder overall

1. Stephan R. Richter
2. Anurag Arnab
3. Shu Liu
4. Bert De Brabandere
5. Vladlen Koltun
6. Luc Van Gool
7. Chien-Yao Wang
8. Davy Neven
9. Yuhui Yuan
10. Weicheng Kuo

Papers from Zeeshan Hayder's perspective

Ordered by how strongly the researchers Zeeshan Hayder 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. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Playing for Benchmarks (2017) — 518 citations
• Boundary-Aware Instance Segmentation (2016) — 160 citations
• Shape-aware Instance Segmentation (2016) — 31 citations
• Structural Kernel Learning for Large Scale Multiclass Object Co-detection (2015) — 8 citations