Kyungbok Min

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 2 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 66 citations into it
• Artificial Intelligence — 47 citations into it
• Model Architectures — 5 citations into it; #2,064 of 2,278 by trust here, #2,078 by citations

Whom Kyungbok Min trusts overall

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

1. Geoffrey E. Hinton
2. Sepp Hochreiter
3. Yoshua Bengio
4. Alex Krizhevsky
5. Xiaodong Yang
6. Kaiming He
7. Oscar D. Lara
8. Oyebade Kayode Oyedotun
9. Yann LeCun
10. Ilya Sutskever

Who trusts Kyungbok Min overall

1. Sakorn Mekruksavanich
2. Weiwei Jiang

Papers from Kyungbok Min's perspective

Ordered by how strongly the researchers Kyungbok Min 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. Long Short-Term Memory
3. ImageNet classification with deep convolutional neural networks
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Going deeper with convolutions
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Deep Learning Approach for Short-Term Stock Trends Prediction Based on Two-Stream Gated Recurrent Unit Network (2018) — 225 citations
• Sensor-based and vision-based human activity recognition: A comprehensive survey (2020) — 652 citations
• A Survey on Internet of Things and Cloud Computing for Healthcare (2019) — 471 citations