Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox
Picture for Antonio Criminisi

Antonio Criminisi

Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement


Jul 31, 2019
Ryutaro Tanno, Daniel Worrall, Enrico Kaden, Aurobrata Ghosh, Francesco Grussu, Alberto Bizzi, Stamatios N. Sotiropoulos, Antonio Criminisi, Daniel C. Alexander

Figure 1 for Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement
Figure 2 for Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement
Figure 3 for Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement
Figure 4 for Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement

  Access Paper or Ask Questions

Deep Learning with Mixed Supervision for Brain Tumor Segmentation


Dec 10, 2018
Pawel Mlynarski, Hervé Delingette, Antonio Criminisi, Nicholas Ayache

Figure 1 for Deep Learning with Mixed Supervision for Brain Tumor Segmentation
Figure 2 for Deep Learning with Mixed Supervision for Brain Tumor Segmentation
Figure 3 for Deep Learning with Mixed Supervision for Brain Tumor Segmentation
Figure 4 for Deep Learning with Mixed Supervision for Brain Tumor Segmentation
* Submitted to SPIE Journal of Medical Imaging 
  Access Paper or Ask Questions

Adaptive Neural Trees


Oct 07, 2018
Ryutaro Tanno, Kai Arulkumaran, Daniel C. Alexander, Antonio Criminisi, Aditya Nori

Figure 1 for Adaptive Neural Trees
Figure 2 for Adaptive Neural Trees
Figure 3 for Adaptive Neural Trees
Figure 4 for Adaptive Neural Trees

  Access Paper or Ask Questions

Semi-Supervised Learning via Compact Latent Space Clustering


Jul 29, 2018
Konstantinos Kamnitsas, Daniel C. Castro, Loic Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya Nori

Figure 1 for Semi-Supervised Learning via Compact Latent Space Clustering
Figure 2 for Semi-Supervised Learning via Compact Latent Space Clustering
Figure 3 for Semi-Supervised Learning via Compact Latent Space Clustering
Figure 4 for Semi-Supervised Learning via Compact Latent Space Clustering
* Presented as a long oral in ICML 2018. Post-conference camera ready 
  Access Paper or Ask Questions

3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context


Jul 23, 2018
Pawel Mlynarski, Hervé Delingette, Antonio Criminisi, Nicholas Ayache

Figure 1 for 3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context
Figure 2 for 3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context
Figure 3 for 3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context
Figure 4 for 3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context
* Submitted to the journal Computerized Medical Imaging and Graphics 
  Access Paper or Ask Questions

Autofocus Layer for Semantic Segmentation


Jun 11, 2018
Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison Cottrell, Antonio Criminisi, Aditya Nori

Figure 1 for Autofocus Layer for Semantic Segmentation
Figure 2 for Autofocus Layer for Semantic Segmentation
Figure 3 for Autofocus Layer for Semantic Segmentation
Figure 4 for Autofocus Layer for Semantic Segmentation
* Published on MICCAI 2018 
  Access Paper or Ask Questions

Measuring Neural Net Robustness with Constraints


Jun 16, 2017
Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya Nori, Antonio Criminisi

Figure 1 for Measuring Neural Net Robustness with Constraints
Figure 2 for Measuring Neural Net Robustness with Constraints
Figure 3 for Measuring Neural Net Robustness with Constraints
Figure 4 for Measuring Neural Net Robustness with Constraints

  Access Paper or Ask Questions

Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution


May 30, 2017
Ryutaro Tanno, Daniel E. Worrall, Aurobrata Ghosh, Enrico Kaden, Stamatios N. Sotiropoulos, Antonio Criminisi, Daniel C. Alexander

Figure 1 for Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution
Figure 2 for Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution
Figure 3 for Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution
Figure 4 for Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution
* Accepted paper at MICCAI 2017 
  Access Paper or Ask Questions

Unsupervised domain adaptation in brain lesion segmentation with adversarial networks


Dec 28, 2016
Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig, Virginia F. J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker

Figure 1 for Unsupervised domain adaptation in brain lesion segmentation with adversarial networks
Figure 2 for Unsupervised domain adaptation in brain lesion segmentation with adversarial networks
Figure 3 for Unsupervised domain adaptation in brain lesion segmentation with adversarial networks
Figure 4 for Unsupervised domain adaptation in brain lesion segmentation with adversarial networks

  Access Paper or Ask Questions

Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups


Nov 30, 2016
Yani Ioannou, Duncan Robertson, Roberto Cipolla, Antonio Criminisi

Figure 1 for Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups
Figure 2 for Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups
Figure 3 for Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups
Figure 4 for Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups
* Updated full version of paper, in full letter paper two-column paper. Includes many textual changes, updated CIFAR10 results, and new analysis of inter/intra-layer correlation 
  Access Paper or Ask Questions

Predicting Personal Traits from Facial Images using Convolutional Neural Networks Augmented with Facial Landmark Information


May 29, 2016
Yoad Lewenberg, Yoram Bachrach, Sukrit Shankar, Antonio Criminisi

Figure 1 for Predicting Personal Traits from Facial Images using Convolutional Neural Networks Augmented with Facial Landmark Information
Figure 2 for Predicting Personal Traits from Facial Images using Convolutional Neural Networks Augmented with Facial Landmark Information
Figure 3 for Predicting Personal Traits from Facial Images using Convolutional Neural Networks Augmented with Facial Landmark Information
Figure 4 for Predicting Personal Traits from Facial Images using Convolutional Neural Networks Augmented with Facial Landmark Information
* 7 pages, 5 figures, IJCAI 2016 
  Access Paper or Ask Questions

Refining Architectures of Deep Convolutional Neural Networks


Apr 22, 2016
Sukrit Shankar, Duncan Robertson, Yani Ioannou, Antonio Criminisi, Roberto Cipolla

Figure 1 for Refining Architectures of Deep Convolutional Neural Networks
Figure 2 for Refining Architectures of Deep Convolutional Neural Networks
Figure 3 for Refining Architectures of Deep Convolutional Neural Networks
Figure 4 for Refining Architectures of Deep Convolutional Neural Networks
* 9 pages, 6 figures, CVPR 2016 
  Access Paper or Ask Questions

Decision Forests, Convolutional Networks and the Models in-Between


Mar 03, 2016
Yani Ioannou, Duncan Robertson, Darko Zikic, Peter Kontschieder, Jamie Shotton, Matthew Brown, Antonio Criminisi

Figure 1 for Decision Forests, Convolutional Networks and the Models in-Between
Figure 2 for Decision Forests, Convolutional Networks and the Models in-Between
Figure 3 for Decision Forests, Convolutional Networks and the Models in-Between
Figure 4 for Decision Forests, Convolutional Networks and the Models in-Between
* Microsoft Research Technical Report 
  Access Paper or Ask Questions

Training CNNs with Low-Rank Filters for Efficient Image Classification


Feb 07, 2016
Yani Ioannou, Duncan Robertson, Jamie Shotton, Roberto Cipolla, Antonio Criminisi

Figure 1 for Training CNNs with Low-Rank Filters for Efficient Image Classification
Figure 2 for Training CNNs with Low-Rank Filters for Efficient Image Classification
Figure 3 for Training CNNs with Low-Rank Filters for Efficient Image Classification
Figure 4 for Training CNNs with Low-Rank Filters for Efficient Image Classification
* International Conference on Learning Representations (ICLR), San Juan, Puerto Rico, 2-4 May 2016 
 * Published as a conference paper at ICLR 2016. v3: updated ICLR status. v2: Incorporated reviewer's feedback including: Amend Fig. 2 and 5 descriptions to explain that there are no ReLUs within the figures. Fix headings of Table 5 - Fix typo in the sentence at bottom of page 6. Add ref. to Predicting Parameters in Deep Learning. Fix Table 6, GMP-LR and GMP-LR-2x had incorrect numbers of filters 
  Access Paper or Ask Questions

WESD - Weighted Spectral Distance for Measuring Shape Dissimilarity


Aug 24, 2012
Ender Konukoglu, Ben Glocker, Antonio Criminisi, Kilian M. Pohl

Figure 1 for WESD - Weighted Spectral Distance for Measuring Shape Dissimilarity
Figure 2 for WESD - Weighted Spectral Distance for Measuring Shape Dissimilarity
Figure 3 for WESD - Weighted Spectral Distance for Measuring Shape Dissimilarity
Figure 4 for WESD - Weighted Spectral Distance for Measuring Shape Dissimilarity

  Access Paper or Ask Questions