Dean C. Barratt

Computer Vision and Pattern Recognition · 2013–2018

A researcher in the Science corpus: 5 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 58 citations into it

Whom Dean C. Barratt trusts

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

1. Jon Gauthier (in Generative Models)
2. Trevor Darrell (in Computer Vision and Pattern Recognition)
3. Kaiming He (in Computer Vision and Pattern Recognition)
4. Shaoqing Ren (in Computer Vision and Pattern Recognition)

Papers from Dean C. Barratt's perspective

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

1. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
2. Rectified Linear Units Improve Restricted Boltzmann Machines
3. Fully convolutional networks for semantic segmentation
4. Identity Mappings in Deep Residual Networks
5. Spatial Transformer Networks
6. Representation Learning: A Review and New Perspectives
7. Context Encoders: Feature Learning by Inpainting
8. Generative Adversarial Networks
9. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
10. Robust Real-time Object Detection

Their papers

• Automatic Multi-organ Segmentation on Abdominal CT with Dense V-networks (2018) — 662 citations
• NiftyNet: a deep-learning platform for medical imaging (2017) — 565 citations
• Weakly-supervised convolutional neural networks for multimodal image registration (2018) — 442 citations
• Intraoperative Organ Motion Models with an Ensemble of Conditional Generative Adversarial Networks (2017) — 16 citations
• Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge (2013) — 882 citations