Dinei A. F. Florêncio

Computer Vision and Pattern Recognition · 2003–2021

A researcher in the Science corpus: 8 papers; trusts 230 researchers and is trusted by 36 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 110 citations into it; #5,079 of 21,575 by trust here, #5,507 by citations
• Artificial Intelligence — 82 citations into it; #6,827 of 35,345 by trust here, #7,471 by citations
• Multimodal Learning — 45 citations into it
• Natural Language Processing — 37 citations into it
• Signal Processing — 24 citations into it; #2,764 of 7,572 by trust here, #2,052 by citations
• Evaluation & Benchmarks — 16 citations into it; #755 of 3,147 by trust here, #1,542 by citations
• Model Architectures — 15 citations into it
• Speech & Audio — 15 citations into it

Whom Dinei A. F. Florêncio trusts overall

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

1. Geoffrey E. Hinton
2. Alex Graves
3. Alex Krizhevsky
4. Yoshua Bengio
5. Kaiming He
6. Jae S. Lim
7. Ilya Sutskever
8. Diederik P. Kingma
9. Dong Yu
10. Yann LeCun

Who trusts Dinei A. F. Florêncio overall

1. Wei Ping
2. Kainan Peng
3. Adam Polyak
4. Edresson Casanova
5. Cormac Herley
6. Zhifeng Kong
7. Joseph Bonneau
8. Yaniv Taigman
9. Felix Kreuk
10. Wei-Ning Hsu

Papers from Dinei A. F. Florêncio's perspective

Ordered by how strongly the researchers Dinei A. F. Florêncio 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• TAP: Text-Aware Pre-training for Text-VQA and Text-Caption (2020) — 164 citations
• TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models (2021) — 682 citations
• CROWDMOS: An approach for crowdsourcing mean opinion score studies (2011) — 280 citations
• LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding (2020) — 702 citations
• Speech Enhancement Using Bayesian Wavenet (2017) — 85 citations
• Speech Enhancement in Multiple-Noise Conditions Using Deep Neural Networks (2016) — 126 citations
• A large-scale study of web password habits (2007) — 1,234 citations
• Improved spread spectrum: a new modulation technique for robust watermarking (2003) — 534 citations