Jonathan Kelly

Computer Vision and Pattern Recognition · with Ablett · 2011–2020

A researcher in the Science corpus: 3 papers; trusts 59 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 27 citations into it; #5,515 of 21,575 by trust here, #12,419 by citations
• Artificial Intelligence — 24 citations into it
• Aerospace Engineering — 19 citations into it; #737 of 6,421 by trust here, #2,828 by citations
• Reinforcement Learning — 16 citations into it
• Robotics & Control — 8 citations into it
• Optimization & Training — 6 citations into it

Whom Jonathan Kelly trusts overall

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

1. Simon Justin Julier
2. David G. Lowe
3. Matthijs C. Dorst
4. Georg S. W. Klein
5. José M. M. Montiel
6. John L. Crassidis
7. Alessandro Chiuso
8. Diederik P. Kingma
9. Andrew J. Davison
10. Jiakai Zhang

Who trusts Jonathan Kelly overall

1. Stephan Weiss
2. Markus Achtelik
3. Guoquan Huang
4. Paul Timothy Furgale
5. Mingyang Li
6. Michael Bloesch
7. Roland Yves Siegwart
8. Giuseppe Loianno
9. Vijay R. Kumar
10. Ke Sun

Papers from Jonathan Kelly's perspective

Ordered by how strongly the researchers Jonathan Kelly 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. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Distinctive Image Features from Scale-Invariant Keypoints
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Visual-Inertial Sensor Fusion: Localization, Mapping and Sensor-to-Sensor Self-calibration (2011) — 570 citations
• Fighting Failures with FIRE: Failure Identification to Reduce Expert Burden in Intervention-Based Learning (2020) — 9 citations
• PROBE-GK: Predictive robust estimation using generalized kernels (2016) — 19 citations