Ricardo Garcia Pinel

Computer Vision and Pattern Recognition · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 365 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 84 citations into it; #18,761 of 21,575 by trust here, #7,092 by citations
• Artificial Intelligence — 70 citations into it; #30,730 of 35,345 by trust here, #10,065 by citations
• Reinforcement Learning — 28 citations into it
• Optimization & Training — 12 citations into it

Whom Ricardo Garcia Pinel trusts overall

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

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

Who trusts Ricardo Garcia Pinel overall

1. Qihang Yu
2. Timo Lüddecke
3. Xueyan Zou
4. Manoj Kumar
5. Bowen Cheng
6. Mostafa Dehghani
7. Ziqi Zhou
8. Qin Liu
9. Tomer Amit
10. Ning Zhang

Papers from Ricardo Garcia Pinel's perspective

Ordered by how strongly the researchers Ricardo Garcia Pinel 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. ImageNet: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Segmenter: Transformer for Semantic Segmentation (2021) — 1,968 citations
• Instruction-driven history-aware policies for robotic manipulations (2022) — 153 citations