Hyungjin Ko

Computer Vision and Pattern Recognition · 2016

A researcher in the Science corpus: 2 papers; trusts 195 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 38 citations into it; #7,612 of 21,575 by trust here, #7,092 by citations
• Artificial Intelligence — 26 citations into it
• Multimodal Learning — 23 citations into it; #443 of 1,211 by trust here, #583 by citations
• Natural Language Processing — 22 citations into it
• Evaluation & Benchmarks — 14 citations into it
• Model Architectures — 11 citations into it
• Optimization & Training — 10 citations into it

Whom Hyungjin Ko trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Kaiming He
4. Chin-Yew Lin
5. Alex Krizhevsky
6. Yoshua Bengio
7. Ilya Sutskever
8. Sepp Hochreiter
9. Jimmy Ba
10. Yann LeCun

Who trusts Hyungjin Ko overall

1. Antoine Miech
2. Youngjae Yu
3. Jianfeng Dong
4. Chris Dongjoo Kim
5. Li Xu
6. Ivan Laptev
7. Gunhee Kim
8. Amir Mazaheri
9. Anna Rohrbach
10. Huaishao Luo

Papers from Hyungjin Ko's perspective

Ordered by how strongly the researchers Hyungjin Ko 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• End-to-End Concept Word Detection for Video Captioning, Retrieval, and Question Answering (2016) — 245 citations
• Video Captioning and Retrieval Models with Semantic Attention (2016) — 46 citations