Kenji Suzuki
Computer Vision and Pattern Recognition · 2003–2017
A researcher in the Science corpus: 4 papers; trusts 43 researchers and is trusted by 21 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 11 citations into it
- Artificial Intelligence — 10 citations into it; #7,285 of 35,345 by trust here, #13,760 by citations
- Pulmonary and Respiratory Medicine — 7 citations into it
- Radiology, Nuclear Medicine and Imaging — 6 citations into it; #265 of 3,265 by trust here, #1,299 by citations
Whom Kenji Suzuki trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Vladimir Naumovich Vapni
- David E. Rumelhart
- Yann LeCun
- Ravi K. Samala
- Steve Lawrence
- Kenny H. Cha
- Alex Krizhevsky
- Pim Moeskops
- Simon Osindero
Who trusts Kenji Suzuki overall
- M. Bakator
- Nagarajan Ganapathy
- Soheila Saeedi
- Sweta Bhattacharya
- Dragica Radosav
- Arvid Lundervold
- Lifeng He
- R. Swaminathan
- Sorayya Rezayi
- S. Rajaraman
Papers from Kenji Suzuki's perspective
Ordered by how strongly the researchers Kenji Suzuki 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)
- 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)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Linear-time connected-component labeling based on sequential local operations (2003) — 467 citations
- Machine Learning in Medical Imaging (2012) — 906 citations
- Overview of deep learning in medical imaging (2017) — 1,082 citations
- Fast connected-component labeling (2009) — 369 citations