Sérgio Pereira

Computer Vision and Pattern Recognition · 2015–2020

A researcher in the Science corpus: 4 papers; trusts 81 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 79 citations into it; #15,624 of 21,575 by trust here, #2,240 by citations
• Artificial Intelligence — 44 citations into it
• Neurology — 20 citations into it; #735 of 1,455 by trust here, #36 by citations
• Model Architectures — 7 citations into it
• Optimization & Training — 7 citations into it
• Media Technology — 6 citations into it

Whom Sérgio Pereira trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yann LeCun
5. Karen Simonyan
6. Kaiming He
7. Ilya Sutskever
8. Andrew L. Maas
9. Xavier Glorot
10. Stefan Bauer

Who trusts Sérgio Pereira overall

1. Enes Ayan
2. Konstantinos Kamnitsas
3. Erico Tjoa
4. Heung-Il Suk
5. Tongxue Zhou
6. Seyed Sadegh Mohseni Salehi
7. Akmalbek Bobomirzaevich Abdusalomov
8. Faisal Mahmood
9. A. Işın
10. Yading Yuan

Papers from Sérgio Pereira's perspective

Ordered by how strongly the researchers Sérgio Pereira 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) (2015) — 6,325 citations
• Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images (2016) — 2,370 citations
• On the Interpretability of Artificial Intelligence in Radiology: Challenges and Opportunities. (2020) — 425 citations
• Understanding and Interpreting Machine Learning in Medical Image Computing Applications (2018) — 82 citations