Sangpil Kim
Computer Vision and Pattern Recognition · with Kim · 2016–2021
A researcher in the Science corpus: 2 papers; trusts 237 researchers and is trusted by 33 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 59 citations into it; #5,302 of 21,575 by trust here, #5,375 by citations
- Artificial Intelligence — 29 citations into it
- Signal Processing — 12 citations into it
- Model Architectures — 11 citations into it
- Optimization & Training — 6 citations into it
Whom Sangpil Kim trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Alex Krizhevsky
- Geoffrey E. Hinton
- Yann LeCun
- Diederik P. Kingma
- Christian Szegedy
- X. Zhang
- Yoshua Bengio
- Ilya Sutskever
- Karen Simonyan
Who trusts Sangpil Kim overall
- Changqian Yu
- Eduardo Romera
- Maxim Berman
- Andres Milioto
- Angela Dai
- Sachin Mehta
- Davy Neven
- Yuenan Hou
- Mennatullah Siam
- Matthias Nießner
Papers from Sangpil Kim's perspective
Ordered by how strongly the researchers Sangpil Kim 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)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation (2016) — 2,375 citations
- Sound-Guided Semantic Image Manipulation (2021) — 54 citations