Joongkyu Kim

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 90 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 34 citations into it
• Artificial Intelligence — 25 citations into it

Whom Joongkyu Kim trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He

Papers from Joongkyu Kim's perspective

Ordered by how strongly the researchers Joongkyu Kim 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. Gradient-based learning applied to document recognition
4. Microsoft COCO: Common Objects in Context
5. ImageNet: A large-scale hierarchical image database
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Fully convolutional networks for semantic segmentation
10. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

Their papers

• Adaptive Prototype Learning and Allocation for Few-Shot Segmentation (2021) — 502 citations