Luiz Oliveira

Computer Vision and Pattern Recognition · 2006–2018

A researcher in the Science corpus: 10 papers; trusts 279 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 79 citations into it; #9,688 of 21,575 by trust here, #6,873 by citations
• Artificial Intelligence — 61 citations into it; #14,634 of 35,345 by trust here, #9,170 by citations
• Safety, Robustness & Interpretability — 16 citations into it
• Model Architectures — 14 citations into it
• Representation & Self-Supervised Learning — 12 citations into it
• Evaluation & Benchmarks — 10 citations into it; #2,445 of 3,147 by trust here, #2,275 by citations
• Media Technology — 7 citations into it
• Optimization & Training — 6 citations into it

Whom Luiz Oliveira 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. David G. Lowe
6. Christian Szegedy
7. Ilya Sutskever
8. Kaiming He
9. Karen Simonyan
10. Diederik P. Kingma

Who trusts Luiz Oliveira overall

1. Dalal Bardou
2. Fabio Alexandre Spanhol
3. Ghulam Murtaza
4. Zhongyi Han
5. Kun Zhang
6. Md. Zahangir Alom
7. Daisuke Komura
8. Alexander Rakhlin
9. Neslihan Bayramoglu
10. Giuseppe Amato

Papers from Luiz Oliveira's perspective

Ordered by how strongly the researchers Luiz Oliveira 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. Gradient-based learning applied to document recognition
4. ImageNet: A large-scale hierarchical image database
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Supervised learning of fuzzy ARTMAP neural networks through particle swarm optimization (2007) — 32 citations
• A Dataset for Breast Cancer Histopathological Image Classification (2016) — 1,610 citations
• PKLot - A robust dataset for parking lot classification (2015) — 313 citations
• Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses (2018) — 327 citations
• Dynamic selection of classifiers - A comprehensive review (2014) — 353 citations
• A Robust Real-Time Automatic License Plate Recognition Based on the YOLO Detector (2018) — 512 citations
• Learning features for offline handwritten signature verification using deep convolutional neural networks (2017) — 344 citations
• Deep features for breast cancer histopathological image classification (2017) — 296 citations
• Breast cancer histopathological image classification using Convolutional Neural Networks (2016) — 838 citations
• An implicit segmentation-based method for recognition of handwritten strings of characters (2006) — 41 citations