Behrooz Mahasseni

Computer Vision and Pattern Recognition · 2013–2017

A researcher in the Science corpus: 3 papers; trusts 592 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 67 citations into it; #6,925 of 21,575 by trust here, #10,677 by citations
• Artificial Intelligence — 34 citations into it; #15,251 of 35,345 by trust here, #20,836 by citations
• Representation & Self-Supervised Learning — 13 citations into it
• Biomedical Engineering — 11 citations into it
• Generative Models — 10 citations into it
• Model Architectures — 10 citations into it; #1,175 of 2,278 by trust here, #1,749 by citations
• Human-Computer Interaction — 6 citations into it
• Signal Processing — 6 citations into it; #4,497 of 7,572 by trust here, #5,086 by citations

Whom Behrooz Mahasseni trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Sepp Hochreiter
4. Alex Krizhevsky
5. Yann LeCun
6. Yoshua Bengio
7. Ilya Sutskever
8. Ruslan Salakhutdinov
9. Kaiming He
10. Nitish Srivastava

Who trusts Behrooz Mahasseni overall

1. Jun Liu
2. Zhiyuan Shi
3. Kaiyang Zhou
4. Zehua Sun
5. Pichao Wang
6. Medhini Narasimhan
7. Zhong Ji
8. Lin Sun
9. Ayush Jaiswal
10. Chandrashekhar Lavania

Papers from Behrooz Mahasseni's perspective

Ordered by how strongly the researchers Behrooz Mahasseni 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. Long Short-Term Memory
5. ImageNet: A large-scale hierarchical image database
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. Going deeper with convolutions

Their papers

• Unsupervised Video Summarization with Adversarial LSTM Networks (2017) — 569 citations
• Regularizing Long Short Term Memory with 3D Human-Skeleton Sequences for Action Recognition (2016) — 166 citations
• Latent Multitask Learning for View-Invariant Action Recognition (2013) — 42 citations