Christine Kroll

Computer Vision and Pattern Recognition · 2015–2016

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 28 citations into it

Whom Christine Kroll trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Ilya Sutskever

Papers from Christine Kroll's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Going deeper with convolutions
3. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
6. Gradient-based learning applied to document recognition
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Long Short-Term Memory
9. ImageNet: A large-scale hierarchical image database
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Hough-CNN: Deep learning for segmentation of deep brain regions in MRI and ultrasound (2016) — 378 citations
• Multimodal image-guided prostate fusion biopsy based on automatic deformable registration (2015) — 75 citations