Joel Kronander

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 2 papers; trusts 175 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 45 citations into it; #16,471 of 21,575 by trust here, #14,151 by citations
• Artificial Intelligence — 16 citations into it
• Model Architectures — 6 citations into it
• Media Technology — 5 citations into it
• Optimization & Training — 5 citations into it

Whom Joel Kronander trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Karen Simonyan
3. Kaiming He
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Yoshua Bengio
7. Andrew Zisserman
8. Ross B. Girshick
9. Sergey Ioffe
10. Yann LeCun

Who trusts Joel Kronander overall

1. Lukas Liebel
2. Sergey I. Nikolenko
3. Yuki Endo
4. Matthias Müller
5. Wencheng Wang
6. Demetris Marnerides
7. Shangzhe Wu
8. Ke Xu

Papers from Joel Kronander's perspective

Ordered by how strongly the researchers Joel Kronander trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. ImageNet Large Scale Visual Recognition Challenge
6. ImageNet: A large-scale hierarchical image database
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Procedural Modeling and Physically Based Rendering for Synthetic Data Generation in Automotive Applications (2017) — 85 citations
• HDR image reconstruction from a single exposure using deep CNNs (2017) — 626 citations