Daniel Ponsa

Computer Vision and Pattern Recognition · 2014–2019

A researcher in the Science corpus: 5 papers; trusts 396 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 97 citations into it; #7,594 of 21,575 by trust here, #6,281 by citations
• Artificial Intelligence — 32 citations into it; #23,797 of 35,345 by trust here, #12,244 by citations
• Aerospace Engineering — 28 citations into it
• Representation & Self-Supervised Learning — 13 citations into it
• Media Technology — 11 citations into it
• ML Systems & Hardware — 6 citations into it
• Model Architectures — 5 citations into it

Whom Daniel Ponsa trusts overall

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

1. David G. Lowe
2. Krystian Mikolajczyk
3. Alex Krizhevsky
4. Cordelia Schmid
5. Geoffrey E. Hinton
6. Kaiming He
7. Yann LeCun
8. Diederik P. Kingma
9. Karen Simonyan
10. Yoshua Bengio

Who trusts Daniel Ponsa overall

1. Rahaf Aljundi
2. Jiayi Ma
3. José Hernandez-Orallo
4. Jérôme Revaud
5. Sergey I. Nikolenko
6. Lukas Pfahler
7. Anastasiia V. Mishchuk

Papers from Daniel Ponsa's perspective

Ordered by how strongly the researchers Daniel Ponsa 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. ImageNet: A large-scale hierarchical image database
6. ImageNet Large Scale Visual Recognition Challenge
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Virtual and Real World Adaptation for Pedestrian Detection (2014) — 194 citations
• Learning local feature descriptors with triplets and shallow convolutional neural networks (2016) — 595 citations
• Kornia: an Open Source Differentiable Computer Vision Library for PyTorch (2019) — 459 citations
• Key.Net: Keypoint Detection by Handcrafted and Learned CNN Filters (2019) — 327 citations
• Virtual and Real World Adaptationfor Pedestrian Detection (2014) — 10 citations