Yoseob Han
Computer Vision and Pattern Recognition · 2017–2020
A researcher in the Science corpus: 5 papers; trusts 237 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 125 citations into it; #16,283 of 21,575 by trust here, #5,082 by citations
- Media Technology — 56 citations into it
- Artificial Intelligence — 40 citations into it
- Radiology, Nuclear Medicine and Imaging — 24 citations into it; #468 of 3,265 by trust here, #1,699 by citations
- Model Architectures — 22 citations into it
- Biomedical Engineering — 16 citations into it; #1,146 of 10,734 by trust here, #4,781 by citations
- Computational Mechanics — 15 citations into it; #7,487 of 10,001 by trust here, #6,582 by citations
- Optimization & Training — 14 citations into it
Whom Yoseob Han trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Andrea Vedaldi
- Alex Krizhevsky
- Kaiming He
- Geoffrey E. Hinton
- Diederik P. Kingma
- Jong Chul Ye
- Ilya Sutskever
- Yoshua Bengio
- Jiang Hsieh
- Jia Deng
Who trusts Yoseob Han overall
- Mingxia Liu
- Jong Chul Ye
- Jinxi Xiang
- Andreas K. Maier
- Hyunseok Seo
- Nahian Alam Siddique
- Mehmet Akçakaya
- Harshit Gupta
- Jaejun Yoo
- A. Chaudhari
Papers from Yoseob Han's perspective
Ordered by how strongly the researchers Yoseob Han trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results (2017) — 1,901 citations
- AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results (2020) — 43 citations
- Framing U-Net via Deep Convolutional Framelets: Application to Sparse-View CT (2017) — 580 citations
- Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems (2017) — 328 citations
- Deep Learning with Domain Adaptation for Accelerated Projection Reconstruction MR (2017) — 245 citations