Jaeyong Sung
Computer Vision and Pattern Recognition · 2011–2015
A researcher in the Science corpus: 4 papers; trusts 394 researchers and is trusted by 56 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 86 citations into it; #3,929 of 21,575 by trust here, #4,030 by citations
- Artificial Intelligence — 52 citations into it; #32,078 of 35,345 by trust here, #15,866 by citations
- Control and Systems Engineering — 24 citations into it; #3,681 of 8,257 by trust here, #1,518 by citations
- Natural Language Processing — 21 citations into it; #5,165 of 5,688 by trust here, #3,282 by citations
- Aerospace Engineering — 19 citations into it
- Reinforcement Learning — 14 citations into it; #2,087 of 2,242 by trust here, #1,395 by citations
- Biomedical Engineering — 11 citations into it
- Robotics & Control — 11 citations into it; #339 of 609 by trust here, #519 by citations
Whom Jaeyong Sung trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Ivan Laptev
- David G. Lowe
- Yoshua Bengio
- Yann LeCun
- Ross B. Girshick
- Thorsten Joachims
- Marc'Aurelio Ranzato
- Kaiming He
Who trusts Jaeyong Sung overall
- Hema Swetha Koppula
- Fei Han
- Ashutosh Saxena
- Runlin Zhao
- Hao Zhang
- Y. Zhu
- Yun Jiang
- Matteo Munaro
- Zhao Yang
- Kai Berger
Papers from Jaeyong Sung's perspective
Ordered by how strongly the researchers Jaeyong Sung 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Unstructured human activity detection from RGBD images (2011) — 577 citations
- Tell me Dave: Context-sensitive grounding of natural language to manipulation instructions (2014) — 309 citations
- Human Activity Detection from RGBD Images (2011) — 355 citations
- Robobarista: Object Part Based Transfer of Manipulation Trajectories from Crowd-Sourcing in 3D Pointclouds (2015) — 71 citations