Robert Haase

Computer Vision and Pattern Recognition · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 22 citations into it

Whom Robert Haase trusts overall

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

1. Álvaro González
2. Kaiming He
3. Yuri Boykov

Papers from Robert Haase's perspective

Ordered by how strongly the researchers Robert Haase 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. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
3. Mask R-CNN
4. ImageNet classification with deep convolutional neural networks
5. Gradient-based learning applied to document recognition
6. TensorFlow: A system for large-scale machine learning
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. ImageNet Large Scale Visual Recognition Challenge
9. Long Short-Term Memory
10. ImageNet: A large-scale hierarchical image database

Their papers

• Labkit: Labeling and Segmentation Toolkit for Big Image Data (2021) — 300 citations
• Star-convex Polyhedra for 3D Object Detection and Segmentation in Microscopy (2019) — 514 citations