Sangil Jung

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 2 papers; trusts 51 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 45 citations into it
• Artificial Intelligence — 39 citations into it
• Efficiency & Compression — 24 citations into it
• Model Architectures — 7 citations into it

Whom Sangil Jung trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Ross B. Girshick
6. X. Zhang
7. Shaoqing Ren
8. Itay Hubara
9. Ilya Sutskever
10. Karen Simonyan

Who trusts Sangil Jung overall

1. Steven K. Esser
2. Yuhang Li
3. Yash Bhalgat
4. Ron Banner
5. Yoonho Boo
6. Jungwook Choi
7. Jing Liu
8. Alexandre D'efossez
9. Ruihao Gong
10. Sungho Shin

Papers from Sangil Jung's perspective

Ordered by how strongly the researchers Sangil Jung 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. Gradient-based learning applied to document recognition
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. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Learning to Quantize Deep Networks by Optimizing Quantization Intervals With Task Loss (2018) — 430 citations
• Joint Training of Low-Precision Neural Network with Quantization Interval Parameters (2018) — 36 citations