Raphael Meier
Computer Vision and Pattern Recognition · 2015–2022
A researcher in the Science corpus: 5 papers; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 78 citations into it
- Artificial Intelligence — 71 citations into it
- Biophysics — 17 citations into it
- Model Architectures — 11 citations into it
- Media Technology — 7 citations into it
Whom Raphael Meier trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Kaiming He
- Geoffrey E. Hinton
- Olaf Ronneberger
- Alex Krizhevsky
- Radford M. Neal
- Yann LeCun
- Yoshua Bengio
- Jimmy Ba
- Ilya Sutskever
Who trusts Raphael Meier overall
Papers from Raphael Meier's perspective
Ordered by how strongly the researchers Raphael Meier trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) (2015) — 6,325 citations
- Federated learning enables big data for rare cancer boundary detection (2022) — 346 citations
- On the Interpretability of Artificial Intelligence in Radiology: Challenges and Opportunities. (2020) — 425 citations
- On the Effect of Inter-observer Variability for a Reliable Estimation of Uncertainty of Medical Image Segmentation (2018) — 124 citations
- Understanding and Interpreting Machine Learning in Medical Image Computing Applications (2018) — 82 citations