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Jump to: Proceedings paper | Thesis
Number of items: 6.
Proceedings paper
Shinoda, S;
Worrall, DE;
Brostow, GJ;
(2017)
Virtual Adversarial Ladder Networks For Semi-supervised Learning.
In:
Proceedings of the NIPS 2017 LLD Workshop.
NIPS 2017 LLD Workshop: Long Beach, CA, USA.
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Tanno, R;
Worrall, DE;
Ghosh, A;
Kaden, E;
Sotiropoulos, SN;
Criminisi, A;
Alexander, DC;
(2017)
Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution.
In: Descoteaux, M and Maier-Hein, L and Franz, A and Jannin, P and Collins, D and Duchesne, S, (eds.)
MICCAI 2017: 20th International Conference, Medical Image Computing and Computer Assisted Intervention: Proceedings, Part I.
(pp. pp. 611-619).
Springer International Publishing: Cham, Switzerland.
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Worrall, DE;
Garbin, SJ;
Turmukhambetov, D;
Brostow, GJ;
(2017)
Interpretable transformations with Encoder-Decoder Networks.
In:
Proceedings of the 2017 IEEE International Conference on Computer Vision (ICCV).
(pp. pp. 5737-5746).
IEEE: Venice, Italy.
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Worrall, DE;
Garbin, SJ;
Turmukhambetov, D;
Brostow, GJ;
(2017)
Harmonic Networks: Deep Translation and Rotation Equivariance.
In:
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
(pp. pp. 7168-7177).
IEEE: Honolulu, HI, USA, USA.
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Worrall, DE;
Wilson, C;
Brostow, GJ;
(2016)
Automated Retinopathy of Prematurity Case Detection with Convolutional Neural Networks.
In: Carneiro, G, (ed.)
Deep Learning and Data Labeling for Medical Applications. LABELS 2016, DLMIA 2016.
(pp. pp. 68-76).
Springer, Cham
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Thesis
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Worrall, Daniel Ernest;
(2019)
Equivariance For Deep Learning And Retinal Imaging.
Doctoral thesis (Ph.D), UCL (University College London).
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