B. Boom

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 2 papers; trusts 259 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 44 citations into it
• Artificial Intelligence — 20 citations into it
• Environmental Engineering — 12 citations into it
• Geology — 12 citations into it
• Computational Mechanics — 9 citations into it
• Meta & Continual Learning — 7 citations into it
• Representation & Self-Supervised Learning — 7 citations into it

Whom B. Boom trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Shaoqing Ren
6. Tsung-Yi Lin
7. Karen Simonyan
8. Yann LeCun
9. Ilya Sutskever
10. Yoshua Bengio

Who trusts B. Boom overall

1. Pei-Hung Chen
2. Yisheng Song
3. Song Tian
4. Guangchen Shi

Papers from B. Boom's perspective

Ordered by how strongly the researchers B. Boom trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Incremental Few-Shot Instance Segmentation (2021) — 92 citations
• SUM: A Benchmark Dataset of Semantic Urban Meshes (2021) — 79 citations