Lachlan Nicholson

Computer Vision and Pattern Recognition · 2016–2018

A researcher in the Science corpus: 3 papers; trusts 247 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 53 citations into it; #8,326 of 21,575 by trust here, #12,419 by citations
• Artificial Intelligence — 22 citations into it; #16,768 of 35,345 by trust here, #23,731 by citations
• Aerospace Engineering — 21 citations into it; #4,911 of 6,421 by trust here, #4,570 by citations
• Evaluation & Benchmarks — 9 citations into it
• Probabilistic & Bayesian Methods — 9 citations into it
• Geology — 8 citations into it

Whom Lachlan Nicholson trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Shaoqing Ren
4. Alex Krizhevsky
5. Geoffrey E. Hinton
6. Yann LeCun
7. Radford M. Neal
8. Karen Simonyan
9. Andrew Zisserman
10. Niko Sünderhauf

Who trusts Lachlan Nicholson overall

1. Di Feng
2. Shichao Yang
3. Antoni Rosinol
4. Ali Harakeh
5. Sebastian A. Scherer
6. Niko Sünderhauf
7. K. J. Joseph
8. Klaus C. J. Dietmayer
9. Dimity Miller
10. Steven L. Waslander

Papers from Lachlan Nicholson's perspective

Ordered by how strongly the researchers Lachlan Nicholson 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. ImageNet Large Scale Visual Recognition Challenge
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Attention is All you Need (Neural Information Processing Systems)
10. Going deeper with convolutions

Their papers

• Dropout Sampling for Robust Object Detection in Open-Set Conditions (2017) — 272 citations
• QuadricSLAM: Dual Quadrics From Object Detections as Landmarks in Object-Oriented SLAM (2018) — 341 citations
• The ACRV picking benchmark: A robotic shelf picking benchmark to foster reproducible research (2016) — 83 citations