Rami Ben-Ari

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 5 papers; trusts 513 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 103 citations into it; #14,837 of 21,575 by trust here, #11,286 by citations
• Artificial Intelligence — 82 citations into it
• Multimodal Learning — 39 citations into it
• Representation & Self-Supervised Learning — 24 citations into it; #2,350 of 3,145 by trust here, #2,042 by citations
• Signal Processing — 18 citations into it
• Evaluation & Benchmarks — 13 citations into it
• Generative Models — 10 citations into it
• Probabilistic & Bayesian Methods — 9 citations into it

Whom Rami Ben-Ari trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Yoshua Bengio
6. Ross B. Girshick
7. Andrew Zisserman
8. Christian Szegedy
9. Ilya Sutskever
10. Yann LeCun

Who trusts Rami Ben-Ari overall

1. Yasufumi Moriya
2. Antoine Miech
3. Alireza Zareian
4. Ramon Sanabria
5. Alex Wang

Papers from Rami Ben-Ari's perspective

Ordered by how strongly the researchers Rami Ben-Ari 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. 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

• Noise Estimation Using Density Estimation for Self-Supervised Multimodal Learning (2020) — 132 citations
• Toward Self-Supervised Object Detection in Unlabeled Videos (2019) — 5 citations
• Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms (2020) — 345 citations
• Learning to Detect and Retrieve Objects From Unlabeled Videos (2019) — 7 citations
• Classification of breast MRI lesions using small-size training sets: comparison of deep learning approaches (2017) — 51 citations