Tim-Oliver Buchholz

Computer Vision and Pattern Recognition · 2018–2021

A researcher in the Science corpus: 2 papers; trusts 54 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 38 citations into it; #17,563 of 21,575 by trust here, #14,151 by citations
• Biophysics — 27 citations into it; #887 of 1,196 by trust here, #696 by citations
• Media Technology — 18 citations into it; #2,826 of 3,621 by trust here, #1,646 by citations
• Artificial Intelligence — 15 citations into it
• Model Architectures — 5 citations into it

Whom Tim-Oliver Buchholz trusts overall

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

1. Stefan Roth
2. Sergey Ioffe
3. Evan Shelhamer
4. Joshua D. Batson
5. Olaf Ronneberger
6. Christian Szegedy
7. Kaiming He
8. A. Buades
9. Kai Zhang
10. Geoffrey E. Hinton

Who trusts Tim-Oliver Buchholz overall

1. Nantheera Anantrasirichai
2. Samuli Laine
3. Yuhui Quan
4. Ke Xu
5. Tao Huang
6. Boyun Li

Papers from Tim-Oliver Buchholz's perspective

Ordered by how strongly the researchers Tim-Oliver Buchholz trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• Noise2Void - Learning Denoising From Single Noisy Images (2018) — 1,490 citations
• Democratising deep learning for microscopy with ZeroCostDL4Mic (2021) — 455 citations