Antonio Loquercio

Computer Vision and Pattern Recognition · 2018–2023

A researcher in the Science corpus: 8 papers; trusts 336 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 129 citations into it; #9,733 of 21,575 by trust here, #8,502 by citations
• Aerospace Engineering — 82 citations into it; #5,423 of 6,421 by trust here, #4,205 by citations
• Artificial Intelligence — 74 citations into it; #19,392 of 35,345 by trust here, #17,776 by citations
• Electrical and Electronic Engineering — 45 citations into it; #10,947 of 16,539 by trust here, #9,902 by citations
• Reinforcement Learning — 37 citations into it
• Robotics & Control — 34 citations into it; #372 of 609 by trust here, #442 by citations
• Probabilistic & Bayesian Methods — 20 citations into it; #1,125 of 1,525 by trust here, #1,313 by citations
• Control and Systems Engineering — 19 citations into it

Whom Antonio Loquercio trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Kaiming He
4. Alex Krizhevsky
5. Yoshua Bengio
6. Karen Simonyan
7. Yann LeCun
8. Jimmy Ba
9. Ilya Sutskever
10. Radford M. Neal

Who trusts Antonio Loquercio overall

1. Elia Kaufmann
2. Maximilian Pichler
3. Davide Scaramuzza
4. Tiago Cortinhal
5. Guillermo Gallego
6. Mattia Segu
7. Daniele Palossi
8. Florian Hartig
9. Jakob Gawlikowski
10. Michael O'Connell

Papers from Antonio Loquercio's perspective

Ordered by how strongly the researchers Antonio Loquercio 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. Long Short-Term Memory
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
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. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• DroNet: Learning to Fly by Driving (2018) — 463 citations
• Deep Drone Racing: Learning Agile Flight in Dynamic Environments (2018) — 154 citations
• Event-Based Vision Meets Deep Learning on Steering Prediction for Self-Driving Cars (2018) — 616 citations
• Champion-level drone racing using deep reinforcement learning (2023) — 875 citations
• End-to-End Learning of Representations for Asynchronous Event-Based Data (2019) — 454 citations
• A 64-mW DNN-Based Visual Navigation Engine for Autonomous Nano-Drones (2018) — 173 citations
• Learning high-speed flight in the wild (2021) — 449 citations
• A General Framework for Uncertainty Estimation in Deep Learning (2019) — 354 citations