Chen Wu
Media Technology · IEEE Transactions on Geoscience and Remote Sensing · 2014–2020
A researcher in the Science corpus: 3 papers; trusts 37 researchers and is trusted by 12 researchers here, as inferred from the citation graph.
Subfields
- Media Technology — 32 citations into it; #1,018 of 3,621 by trust here, #1,598 by citations
- Atmospheric Science — 18 citations into it; #1,655 of 4,804 by trust here, #2,779 by citations
- Computer Vision and Pattern Recognition — 18 citations into it
- Artificial Intelligence — 14 citations into it; #27,177 of 35,345 by trust here, #27,551 by citations
- Ecology — 14 citations into it
- Analytical Chemistry — 12 citations into it
- Cognitive Neuroscience — 6 citations into it
- Signal Processing — 6 citations into it
Whom Chen Wu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Allan Aasbjerg Nielsen
- Lorenzo Bruzzone
- Francesca Bovolo
- Zhang Zhang
- Jinsong Deng
- Turgay Çelik
- Diederik P. Kingma
- Laurenz Wiskott
- Diego Fernández-Prieto
- Kaiming He
Who trusts Chen Wu overall
- Hongruixuan Chen
- Yuxing Chen
- Bo Du
- Xu Peng
- Haobo Lyu
- Lorenzo Bruzzone
- Lichao Mou
- Ayesha Shafique
- Ruofei Zhong
- Hui Lu
Papers from Chen Wu's perspective
Ordered by how strongly the researchers Chen Wu 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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
- Slow Feature Analysis for Change Detection in Multispectral Imagery (2014) — 329 citations
- Change Detection in Multisource VHR Images via Deep Siamese Convolutional Multiple-Layers Recurrent Neural Network (2020) — 315 citations
- Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-Temporal Remote Sensing Images (2018) — 308 citations