| Support vector machines for classification and regression SR Gunn ISIS technical report 14, 1998 | 5548* | 1998 |
| Feature extraction I Guyon, S Gunn, M Nikravesh, L Zadeh Foundations and applications, 2006 | 3830* | 2006 |
| Result analysis of the nips 2003 feature selection challenge I Guyon, S Gunn, A Ben-Hur, G Dror Advances in Neural Information Processing Systems, 545-552, 2004 | 872 | 2004 |
| Positron emission tomography compartmental models RN Gunn, SR Gunn, VJ Cunningham Journal of Cerebral Blood Flow & Metabolism 21 (6), 635-652, 2001 | 614 | 2001 |
| Band selection for hyperspectral image classification using mutual information B Guo, SR Gunn, RI Damper, JDB Nelson Geoscience and Remote Sensing Letters, IEEE 3 (4), 522-526, 2006 | 483 | 2006 |
| A robust snake implementation; a dual active contour SR Gunn, MS Nixon Pattern Analysis and Machine Intelligence, IEEE Transactions on 19 (1), 63-68, 1997 | 337 | 1997 |
| Linear spectral mixture models and support vector machines for remote sensing M Brown, HG Lewis, SR Gunn Geoscience and Remote Sensing, IEEE Transactions on 38 (5), 2346-2360, 2000 | 311 | 2000 |
| Positron Emission Tomography Compartmental Models: A Basis Pursuit Strategy for Kinetic Modeling RN Gunn, SR Gunn, FE Turkheimer, JAD Aston, VJ Cunningham Journal of Cerebral Blood Flow & Metabolism 22 (12), 1425-1439, 2002 | 294 | 2002 |
| Customizing kernel functions for SVM-based hyperspectral image classification B Guo, SR Gunn, RI Damper, JDB Nelson Image Processing, IEEE Transactions on 17 (4), 622-629, 2008 | 223 | 2008 |
| Support vector machines for optimal classification and spectral unmixing M Brown, SR Gunn, HG Lewis Ecological Modelling 120 (2), 167-179, 1999 | 188 | 1999 |
| A probabilistic framework for SVM regression and error bar estimation JB Gao, SR Gunn, CJ Harris, M Brown Machine Learning 46 (1-3), 71-89, 2002 | 185 | 2002 |
| Network performance assessment for neurofuzzy data modelling SR Gunn, M Brown, KM Bossley Advances in Intelligent Data Analysis Reasoning About Data, 313-323, 1997 | 180 | 1997 |
| A fast separability-based feature-selection method for high-dimensional remotely sensed image classification B Guo, RI Damper, SR Gunn, JDB Nelson Pattern Recognition 41 (5), 1653-1662, 2008 | 169 | 2008 |
| Identifying feature relevance using a random forest J Rogers, S Gunn Subspace, Latent Structure and Feature Selection, 173-184, 2006 | 164 | 2006 |
| Structural modelling with sparse kernels SR Gunn, JS Kandola Machine learning 48 (1-3), 137-163, 2002 | 133 | 2002 |
| On the discrete representation of the Laplacian of Gaussian SR Gunn Pattern Recognition 32 (8), 1463-1472, 1999 | 126 | 1999 |
| Machine learning can improve prediction of severity in acute pancreatitis using admission values of APACHE II score and C-reactive protein CB Pearce, SR Gunn, A Ahmed, CD Johnson Pancreatology 6 (1-2), 123-131, 2006 | 119 | 2006 |
| The relevance vector machine technique for channel equalization application S Chen, SR Gunn, CJ Harris IEEE Transactions on neural networks 12 (6), 1529-1532, 2001 | 92 | 2001 |
| Lightweight PUF-based authentication protocol for IoT devices Y Yilmaz, SR Gunn, B Halak 2018 IEEE 3rd international verification and security workshop (IVSW), 38-43, 2018 | 88 | 2018 |
| Handwritten Chinese radical recognition using nonlinear active shape models D Shi, SR Gunn, RI Damper IEEE transactions on pattern analysis and machine intelligence 25 (2), 277-280, 2003 | 87 | 2003 |
