Heechul Jung

Computer Vision and Pattern Recognition · 2015–2020

A researcher in the Science corpus: 5 papers; trusts 367 researchers and is trusted by 26 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 86 citations into it; #5,781 of 21,575 by trust here, #4,584 by citations
• Artificial Intelligence — 56 citations into it; #9,913 of 35,345 by trust here, #9,465 by citations
• Representation & Self-Supervised Learning — 35 citations into it
• Model Architectures — 18 citations into it
• Optimization & Training — 14 citations into it
• Media Technology — 5 citations into it

Whom Heechul Jung trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Yann LeCun
4. Yoshua Bengio
5. Kaiming He
6. Ilya Sutskever
7. Ian J. Goodfellow
8. Karen Simonyan
9. Nitish Srivastava
10. Benjamin Goodrich

Who trusts Heechul Jung overall

1. Marc Masana
2. Fei Ye
3. Jiangpeng He
4. Shan Li
5. Gyuhak Kim
6. Zheda Mai
7. ByoungChul Ko
8. Saihui Hou
9. Ramakanth Pasunuru
10. Adrian G. Bors

Papers from Heechul Jung's perspective

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

Their papers

• Less-forgetting Learning in Deep Neural Networks (2016) — 242 citations
• Rotating your face using multi-task deep neural network (2015) — 297 citations
• Joint Fine-Tuning in Deep Neural Networks for Facial Expression Recognition (2015) — 676 citations
• FixBi: Bridging Domain Spaces for Unsupervised Domain Adaptation (2020) — 266 citations
• Less-forgetful Learning for Domain Expansion in Deep Neural Networks (2017) — 78 citations