Hazem Wannous

Computer Vision and Pattern Recognition · 2013–2015

A researcher in the Science corpus: 5 papers; trusts 147 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 84 citations into it; #6,603 of 21,575 by trust here, #6,671 by citations
• Human-Computer Interaction — 43 citations into it; #636 of 2,253 by trust here, #468 by citations
• Artificial Intelligence — 29 citations into it
• Biomedical Engineering — 28 citations into it; #3,804 of 10,734 by trust here, #4,405 by citations
• 3D Vision & Pose — 19 citations into it; #635 of 689 by trust here, #558 by citations
• Endocrinology, Diabetes and Metabolism — 9 citations into it
• Geometry and Topology — 7 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Hazem Wannous trusts overall

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

1. Xiaodong Yang
2. Zicheng Liu
3. Lu Xia
4. Wanqing Li
5. Omar Oreifej
6. Pavan K. Turaga
7. Jiang Wang
8. Yingli Tian
9. Chih-Jen Lin
10. Zhengyou Zhang

Who trusts Hazem Wannous overall

1. Liliana Lo Presti
2. Fei Han
3. Jun Liu
4. Boulbaba Ben Amor
5. Diogo Carbonera Luvizon
6. Marco La Cascia
7. Pichao Wang
8. Brian Reily
9. Qianli Ma
10. Jingyong Su

Papers from Hazem Wannous's perspective

Ordered by how strongly the researchers Hazem Wannous 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. ImageNet: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Going deeper with convolutions
9. Attention is All you Need (Neural Information Processing Systems)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Accurate 3D action recognition using learning on the Grassmann manifold (2015) — 200 citations
• Space-Time Pose Representation for 3D Human Action Recognition (2013) — 72 citations
• Combined shape analysis of human poses and motion units for action segmentation and recognition (2015) — 19 citations
• Human Action Recognition by Shape Analysis of Motion Trajectories on Riemannian Manifold (2014)
• Grassmannian Representation of Motion Depth for 3D Human Gesture and Action Recognition (2014) — 37 citations