Generative adversarial networks: An overview A Creswell, T White, V Dumoulin, K Arulkumaran, B Sengupta, ... IEEE signal processing magazine 35 (1), 53-65, 2018 | 4370 | 2018 |
Deep reinforcement learning: A brief survey K Arulkumaran, MP Deisenroth, M Brundage, AA Bharath IEEE Signal Processing Magazine 34 (6), 26-38, 2017 | 3766 | 2017 |
A brief survey of deep reinforcement learning K Arulkumaran, MP Deisenroth, M Brundage, AA Bharath arXiv preprint arXiv:1708.05866, 2017 | 1085 | 2017 |
Segmentation of blood vessels from red-free and fluorescein retinal images ME Martinez-Perez, AD Hughes, SA Thom, AA Bharath, KH Parker Medical image analysis 11 (1), 47-61, 2007 | 595 | 2007 |
Inverting the generator of a generative adversarial network A Creswell, AA Bharath IEEE transactions on neural networks and learning systems 30 (7), 1967-1974, 2018 | 403 | 2018 |
Retinal vascular tree morphology: a semi-automatic quantification ME Martinez-Perez, AD Highes, AV Stanton, SA Thorn, N Chapman, ... IEEE Transactions on Biomedical Engineering 49 (8), 912-917, 2002 | 353 | 2002 |
Carotid artery wall motion estimated from B-mode ultrasound using region tracking and block matching S Golemati, A Sassano, MJ Lever, AA Bharath, S Dhanjil, AN Nicolaides Ultrasound in medicine & biology 29 (3), 387-399, 2003 | 247 | 2003 |
Retinal blood vessel segmentation by means of scale-space analysis and region growing ME Martínez-Pérez, AD Hughes, AV Stanton, SA Thom, AA Bharath, ... Medical Image Computing and Computer-Assisted Intervention–MICCAI’99: Second …, 1999 | 237 | 1999 |
Denoising adversarial autoencoders A Creswell, AA Bharath IEEE transactions on neural networks and learning systems 30 (4), 968-984, 2018 | 167 | 2018 |
Computer algorithms for the automated measurement of retinal arteriolar diameters N Chapman, N Witt, X Gao, AA Bharath, AV Stanton, SA Thom, ... British Journal of Ophthalmology 85 (1), 74-79, 2001 | 163 | 2001 |
Robust cell nuclei segmentation using statistical modelling T Mouroutis, SJ Roberts, AA Bharath Bioimaging 6 (2), 79-91, 1998 | 132 | 1998 |
A method of vessel tracking for vessel diameter measurement on retinal images X Gao, A Bharath, A Stanton, A Hughes, N Chapman, S Thom Proceedings 2001 International Conference on Image Processing (Cat. No …, 2001 | 124 | 2001 |
A steerable complex wavelet construction and its application to image denoising AA Bharath, J Ng IEEE Transactions on Image Processing 14 (7), 948-959, 2005 | 110 | 2005 |
On denoising autoencoders trained to minimise binary cross-entropy A Creswell, K Arulkumaran, AA Bharath arXiv preprint arXiv:1708.08487, 2017 | 107 | 2017 |
Scale-space analysis for the characterisation of retinal blood vessels M Martínez-Pérez Medical image computing and computer-assisted intervention-MICCAI'99, 90-97, 1999 | 104 | 1999 |
Quantification and characterisation of arteries in retinal images XW Gao, A Bharath, A Stanton, A Hughes, N Chapman, S Thom Computer methods and programs in biomedicine 63 (2), 133-146, 2000 | 97 | 2000 |
Adversarial training for sketch retrieval A Creswell, AA Bharath European Conference on Computer Vision, 798-809, 2016 | 73 | 2016 |
Segmentation of retinal blood vessels based on the second directional derivative and region growing ME Martinez-Perez, AD Hughes, AV Stanton, SA Thom, AA Bharath, ... Proceedings 1999 International Conference on Image Processing (Cat …, 1999 | 66 | 1999 |
A data augmentation methodology for training machine/deep learning gait recognition algorithms CC Charalambous, AA Bharath arXiv preprint arXiv:1610.07570, 2016 | 63 | 2016 |
Multi-scale rotation-equivariant graph neural networks for unsteady Eulerian fluid dynamics M Lino, S Fotiadis, AA Bharath, CD Cantwell Physics of Fluids 34 (8), 2022 | 60 | 2022 |