| Deep reinforcement learning: A brief survey K Arulkumaran, MP Deisenroth, M Brundage, AA Bharath IEEE Signal Processing Magazine 34 (6), 26-38, 2017 | 2147 | 2017 |
| Generative adversarial networks: An overview A Creswell, T White, V Dumoulin, K Arulkumaran, B Sengupta, ... IEEE signal processing magazine 35 (1), 53-65, 2018 | 2068 | 2018 |
| A brief survey of deep reinforcement learning K Arulkumaran, MP Deisenroth, M Brundage, AA Bharath arXiv preprint arXiv:1708.05866, 2017 | 789 | 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 | 561 | 2007 |
| 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 | 335 | 2002 |
| 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 | 310 | 2018 |
| 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 | 234 | 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 | 228 | 1999 |
| 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 | 156 | 2001 |
| Robust cell nuclei segmentation using statistical modelling T Mouroutis, SJ Roberts, AA Bharath Bioimaging 6 (2), 79-91, 1998 | 133 | 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 | 122 | 2001 |
| Denoising adversarial autoencoders A Creswell, AA Bharath IEEE transactions on neural networks and learning systems 30 (4), 968-984, 2018 | 120 | 2018 |
| 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 | 105 | 2005 |
| Scale-space analysis for the characterization of retinal blood vessels M Martínez-Pérez Medical image computing and computer-assisted intervention-MICCAI'99, 90-97, 1999 | 101 | 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 | 94 | 2000 |
| On denoising autoencoders trained to minimise binary cross-entropy A Creswell, K Arulkumaran, AA Bharath arXiv preprint arXiv:1708.08487, 2017 | 69 | 2017 |
| 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 | 64 | 1999 |
| Adversarial training for sketch retrieval A Creswell, AA Bharath European Conference on Computer Vision, 798-809, 2016 | 60 | 2016 |
| A data augmentation methodology for training machine/deep learning gait recognition algorithms CC Charalambous, AA Bharath arXiv preprint arXiv:1610.07570, 2016 | 57 | 2016 |
| Rethinking multiscale cardiac electrophysiology with machine learning and predictive modelling CD Cantwell, Y Mohamied, KN Tzortzis, S Garasto, C Houston, ... Computers in biology and medicine 104, 339-351, 2019 | 46 | 2019 |
Stephen RobertsProfessor of Engineering Science (Machine Learning, Information Engineering), University of OxfordVerified email at robots.ox.ac.uk
