Le Wang
Media Technology · with Chen · 2004–2022
A researcher in the Science corpus: 6 papers; trusts 45 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Media Technology — 50 citations into it; #1,194 of 3,621 by trust here, #1,423 by citations
- Atmospheric Science — 34 citations into it; #1,162 of 4,804 by trust here, #2,179 by citations
- Ecology — 29 citations into it; #2,395 of 10,717 by trust here, #6,392 by citations
- Global and Planetary Change — 24 citations into it
- Computer Vision and Pattern Recognition — 20 citations into it
- Artificial Intelligence — 17 citations into it
- Analytical Chemistry — 10 citations into it
- Environmental Engineering — 6 citations into it
Whom Le Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Lorenzo Bruzzone
- Yann LeCun
- S. Smolander
- Chaichoke Vaiphasa
- Chein-I. Chang
- Yoshua Bengio
- Geoffrey E. Hinton
- Nirmal Keshava
- Philip E. Dennison
- Philip Lewis
Who trusts Le Wang overall
- Andrea S. Laliberte
- Jason W. Karl
- Minho Kim
- David Gudex‐Cross
- Miao Li
- Albert Rango
- Brian A. Maurer
- E. Aptoula
- Thomas Blaschke
- Marguerite Madden
Papers from Le Wang's perspective
Ordered by how strongly the researchers Le Wang 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)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Going deeper with convolutions
Their papers
- Deep learning for change detection in remote sensing: a review (2022) — 325 citations
- Change Detection in Multisource VHR Images via Deep Siamese Convolutional Multiple-Layers Recurrent Neural Network (2020) — 315 citations
- Modeling land price distribution using multifractal IDW interpolation and fractal filtering method (2013) — 67 citations
- Retrieval of subpixel Tamarix canopy cover from Landsat data along the Forgotten River using linear and nonlinear spectral mixture models (2010) — 57 citations
- Evaluation of Morphological Texture Features for Mangrove Forest Mapping and Species Discrimination Using Multispectral IKONOS Imagery (2009) — 127 citations
- Integration of object-based and pixel-based classification for mapping mangroves with IKONOS imagery (2004) — 463 citations