Roman Kaskman

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 96 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 56 citations into it; #20,889 of 21,575 by trust here, #15,955 by citations
• Artificial Intelligence — 30 citations into it; #34,320 of 35,345 by trust here, #24,417 by citations

Whom Roman Kaskman trusts overall

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

1. Joseph Redmon
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Kaiming He
5. Ross B. Girshick
6. Karen Simonyan
7. Piotr Doll'ar
8. Ilya Sutskever
9. Yoshua Bengio
10. Shaoqing Ren

Who trusts Roman Kaskman overall

1. Yan Zhang
2. Jonathon S. Hare

Papers from Roman Kaskman's perspective

Ordered by how strongly the researchers Roman Kaskman 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet Large Scale Visual Recognition Challenge
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. ImageNet: A large-scale hierarchical image database
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Deep Perm-Set Net: Learn to predict sets with unknown permutation and cardinality using deep neural networks (2018) — 26 citations
• Learn to Predict Sets Using Feed-Forward Neural Networks (2020) — 21 citations