Josien P. W. Pluim
Computer Vision and Pattern Recognition · 2000–2020
A researcher in the Science corpus: 21 papers; trusts 63 researchers and is trusted by 61 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 174 citations into it; #3,663 of 21,575 by trust here, #2,478 by citations
- Radiology, Nuclear Medicine and Imaging — 88 citations into it; #232 of 3,265 by trust here, #154 by citations
- Artificial Intelligence — 78 citations into it; #17,998 of 35,345 by trust here, #5,059 by citations
- Ophthalmology — 27 citations into it; #166 of 222 by trust here, #200 by citations
- Biomedical Engineering — 21 citations into it; #1,575 of 10,734 by trust here, #2,264 by citations
- Molecular Biology — 17 citations into it
- Aerospace Engineering — 11 citations into it
- Computational Mechanics — 11 citations into it
Whom Josien P. W. Pluim trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Paul A. Viola
- Philippe Thévenaz
- J. B. Antoine Maintz
- Michael A. Unser
- Mark Jenkinson
- William M. Wells
- Luis Freire
- Daniel Rueckert
- Max A. Viergever
- Stefan Klein
Who trusts Josien P. W. Pluim overall
- Francisco P. M. Oliveira
- Stefan Klein
- Aristeidis Sotiras
- A. Gholipour
- Mark Paul Wachowiak
- Max A. Viergever
- João Manuel Ribeiro da Silva Tavares
- Shijun Wang
- Ryan W. Wolcott
- Sahil Suri
Papers from Josien P. W. Pluim's perspective
Ordered by how strongly the researchers Josien P. W. Pluim trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Mutual-information-based registration of medical images: a survey (2003) — 3,257 citations
- Not‐so‐supervised: A survey of semi‐supervised, multi‐instance, and transfer learning in medical image analysis (2018) — 897 citations
- Assessment of algorithms for mitosis detection in breast cancer histopathology images (2014) — 464 citations
- Evaluation of Optimization Methods for Nonrigid Medical Image Registration Using Mutual Information and B-Splines (2007) — 511 citations
- Roto-Translation Covariant Convolutional Networks for Medical Image Analysis (2018) — 199 citations
- Adaptive Stochastic Gradient Descent Optimisation for Image Registration (2009) — 457 citations
- Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge (2011) — 492 citations
- Automatic segmentation of the prostate in 3D MR images by atlas matching using localized mutual information. (2008) — 460 citations
- Image registration (2003) — 531 citations
- clDice - a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation (2020) — 549 citations
- Predicting breast tumor proliferation from whole‐slide images: The TUPAC16 challenge (2018) — 307 citations
- Evaluation of a deep learning approach for the segmentation of brain tissues and white matter hyperintensities of presumed vascular origin in MRI (2017) — 79 citations
- Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores (2016) — 407 citations
- A survey of medical image registration - under review (2016) — 286 citations
- Gland segmentation in colon histology images: The glas challenge contest (2016) — 1,012 citations
- Breast Cancer Histopathology Image Analysis: A Review (2014) — 652 citations
- Automatic Nuclei Segmentation in H&E Stained Breast Cancer Histopathology Images (2013) — 395 citations
- elastix: A Toolbox for Intensity-Based Medical Image Registration (2010) — 4,197 citations
- Medical Image Computing and Computer-Assisted Intervention - MICCAI 2010, 13th International Conference, Beijing, China, September 20-24, 2010, Proceedings, Part III (2010) — 353 citations
- Image registration by maximization of combined mutual information and gradient information (2000) — 818 citations