Steven C. Y. Hung
Computer Vision and Pattern Recognition · 2019
A researcher in the Science corpus: 2 papers; trusts 72 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 49 citations into it; #12,381 of 21,575 by trust here, #6,795 by citations
- Artificial Intelligence — 35 citations into it; #19,808 of 35,345 by trust here, #9,641 by citations
- Representation & Self-Supervised Learning — 19 citations into it
- Signal Processing — 9 citations into it
- Efficiency & Compression — 8 citations into it
Whom Steven C. Y. Hung trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Arun Mallya
- Andrew Zisserman
- Kaiming He
- Ilya Sutskever
- Yoshua Bengio
- Christian Szegedy
- Yann LeCun
- Diederik P. Kingma
Who trusts Steven C. Y. Hung overall
- Sen Lin
- Gyuhak Kim
- Prashant Bhat
- Li Yang
- Jorge Armando Mendez Mendez
- Diana Benavides Prado
- Nikhil Mehta
- Yiduo Guo
- Lemeng Wu
- Arthur Douillard
Papers from Steven C. Y. Hung's perspective
Ordered by how strongly the researchers Steven C. Y. Hung 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)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Compacting, Picking and Growing for Unforgetting Continual Learning (2019) — 379 citations
- Increasingly Packing Multiple Facial-Informatics Modules in A Unified Deep-Learning Model via Lifelong Learning (2019) — 47 citations