Shihong Du
Computer Vision and Pattern Recognition · 2016
A researcher in the Science corpus: 3 papers; trusts 244 researchers and is trusted by 67 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 38 citations into it; #3,881 of 21,575 by trust here, #9,872 by citations
- Media Technology — 32 citations into it; #185 of 3,621 by trust here, #612 by citations
- Atmospheric Science — 20 citations into it; #88 of 4,804 by trust here, #987 by citations
- Artificial Intelligence — 9 citations into it
- Representation & Self-Supervised Learning — 8 citations into it
- Ecology — 7 citations into it; #1,293 of 10,717 by trust here, #6,072 by citations
- Ocean Engineering — 5 citations into it
Whom Shihong Du trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David G. Lowe
- Wenzhi Zhao
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yi Yang
- Yann LeCun
- Kunihiko Fukushima
- Navneet Dalal
- Yoshua Bengio
- Ilya Sutskever
Who trusts Shihong Du overall
- Wenzhi Zhao
- Nicolas Audebert
- Jingxiang Yang
- Shutao Li
- Alberto Signoroni
- Mercedes Eugenia Paoletti
- Pedram Ghamisi
- Ava Vali
- Xiaohui Yuan
- Weiwei Song
Papers from Shihong Du's perspective
Ordered by how strongly the researchers Shihong Du 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
- Long Short-Term Memory
- 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)
- Going deeper with convolutions
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Learning multiscale and deep representations for classifying remotely sensed imagery (2016) — 375 citations
- Spectral–Spatial Feature Extraction for Hyperspectral Image Classification: A Dimension Reduction and Deep Learning Approach (2016) — 1,136 citations
- Scene classification using multi-scale deeply described visual words (2016) — 55 citations