Timm Haucke

Computer Vision and Pattern Recognition · 2021–2022

A researcher in the Science corpus: 4 papers; trusts 417 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 64 citations into it; #12,419 of 21,575 by trust here, #17,757 by citations
• Ecology — 23 citations into it; #10,505 of 10,717 by trust here, #10,333 by citations
• Artificial Intelligence — 20 citations into it
• Model Architectures — 17 citations into it
• Ecological Modeling — 12 citations into it; #2,451 of 2,530 by trust here, #2,444 by citations
• Evaluation & Benchmarks — 12 citations into it
• Media Technology — 9 citations into it
• 3D Vision & Pose — 7 citations into it; #473 of 689 by trust here, #648 by citations

Whom Timm Haucke trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. René Ranftl
4. Jia Deng
5. Ross B. Girshick
6. Geoffrey E. Hinton
7. Sara Beery
8. J. Marcus Rowcliffe
9. X. Zhang
10. Shaoqing Ren

Who trusts Timm Haucke overall

1. Peter Johanns
2. Volker Steinhage
3. Hjalmar S. Kühl
4. Valentin Gabeur

Papers from Timm Haucke's perspective

Ordered by how strongly the researchers Timm Haucke 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• SOCRATES: Introducing Depth in Visual Wildlife Monitoring Using Stereo Vision (2022) — 13 citations
• Exploiting Depth Information for Wildlife Monitoring (2021) — 16 citations
• Automated distance estimation for wildlife camera trapping (2022) — 26 citations
• Overcoming the distance estimation bottleneck in estimating animal abundance with camera traps (2021) — 28 citations