Rizwan Ahmed Chaudhry

Computer Vision and Pattern Recognition · 2009–2013

A researcher in the Science corpus: 4 papers; trusts 223 researchers and is trusted by 39 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 48 citations into it; #4,482 of 21,575 by trust here, #3,476 by citations
• Artificial Intelligence — 18 citations into it; #33,685 of 35,345 by trust here, #8,999 by citations
• Biomedical Engineering — 10 citations into it; #2,013 of 10,734 by trust here, #2,547 by citations
• Signal Processing — 7 citations into it
• Human-Computer Interaction — 6 citations into it; #323 of 2,253 by trust here, #206 by citations
• Control and Systems Engineering — 5 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Rizwan Ahmed Chaudhry trusts overall

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

1. Bernhard Schölkopf
2. Geoffrey E. Hinton
3. Ivan Laptev
4. Alex Krizhevsky
5. Kaiming He
6. Yoshua Bengio
7. Diederik P. Kingma
8. Jitendra Malik
9. Alexei A. Efros
10. Yann LeCun

Who trusts Rizwan Ahmed Chaudhry overall

1. Liliana Lo Presti
2. Yong Du
3. Gurkirt Singh
4. Fei Han
5. Jun Liu
6. Suraj Vantigodi
7. José Ramón Padilla-López
8. Cheng Chen
9. Roozbeh Jafari
10. Qiuhong Ke

Papers from Rizwan Ahmed Chaudhry's perspective

Ordered by how strongly the researchers Rizwan Ahmed Chaudhry 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. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
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

• Berkeley MHAD: A comprehensive Multimodal Human Action Database (2013) — 515 citations
• Histograms of oriented optical flow and Binet-Cauchy kernels on nonlinear dynamical systems for the recognition of human actions (2009) — 720 citations
• Bio-inspired Dynamic 3D Discriminative Skeletal Features for Human Action Recognition (2013) — 166 citations
• Sequence of the Most Informative Joints (SMIJ): A new representation for human skeletal action recognition (2012) — 404 citations