Nicholas J. Durr

Computer Vision and Pattern Recognition · 2007–2018

A researcher in the Science corpus: 3 papers; trusts 123 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 60 citations into it; #17,622 of 21,575 by trust here, #10,334 by citations
• Artificial Intelligence — 38 citations into it; #28,675 of 35,345 by trust here, #15,236 by citations
• Biophysics — 25 citations into it
• Radiology, Nuclear Medicine and Imaging — 22 citations into it
• Generative Models — 14 citations into it
• Media Technology — 8 citations into it
• Medical Imaging — 8 citations into it
• Model Architectures — 5 citations into it

Whom Nicholas J. Durr trusts overall

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

1. Kaiming He
2. Individualized Treat
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Diederik P. Kingma
6. Jelmer M. Wolterink
7. Olaf Ronneberger
8. Yoshua Bengio
9. Ilya Sutskever
10. Yann LeCun

Who trusts Nicholas J. Durr overall

1. Xiaohua Huang
2. Hsiangkuo Yuan
3. Nikolai G. Khlebtsov
4. Garrett Wilson

Papers from Nicholas J. Durr's perspective

Ordered by how strongly the researchers Nicholas J. Durr 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. GENERATIVE ADVERSARIAL NETS
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. ImageNet Large Scale Visual Recognition Challenge
9. Attention is All you Need (Neural Information Processing Systems)
10. Microsoft COCO: Common Objects in Context

Their papers

• Deep Adversarial Training for Multi-Organ Nuclei Segmentation in Histopathology Images (2018) — 331 citations
• Two-photon luminescence imaging of cancer cells using molecularly targeted gold nanorods. (2007) — 860 citations
• Unsupervised Reverse Domain Adaptation for Synthetic Medical Images via Adversarial Training (2017) — 266 citations