Dimity Miller

Computer Vision and Pattern Recognition · 2017–2018

A researcher in the Science corpus: 3 papers; trusts 311 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 62 citations into it; #10,366 of 21,575 by trust here, #13,542 by citations
• Artificial Intelligence — 52 citations into it; #10,726 of 35,345 by trust here, #17,776 by citations
• Safety, Robustness & Interpretability — 17 citations into it
• Evaluation & Benchmarks — 16 citations into it
• Probabilistic & Bayesian Methods — 16 citations into it
• Aerospace Engineering — 7 citations into it

Whom Dimity Miller trusts overall

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

1. Radford M. Neal
2. Alex Kendall
3. Ross B. Girshick
4. Kaiming He
5. Yarin Gal
6. Geoffrey E. Hinton
7. Antonio Torralba
8. Alex Krizhevsky
9. Karen Simonyan
10. Shaoqing Ren

Who trusts Dimity Miller overall

1. Di Feng
2. Xuefeng Du
3. K. J. Joseph
4. Niko Sünderhauf
5. David Hall
6. Feras Dayoub
7. Lachlan Nicholson
8. Zhaoning Wang
9. Lars Rosenbaum
10. Klaus C. J. Dietmayer

Papers from Dimity Miller's perspective

Ordered by how strongly the researchers Dimity Miller 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
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. Going deeper with convolutions

Their papers

• Dropout Sampling for Robust Object Detection in Open-Set Conditions (2017) — 272 citations
• Probabilistic Object Detection: Definition and Evaluation (2018) — 128 citations
• Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection (2018) — 119 citations