2009 |
32 | EE | James D. B. Nelson,
Robert I. Damper,
Steve R. Gunn,
Baofeng Guo:
A signal theory approach to support vector classification: The sinc kernel.
Neural Networks 22(1): 49-57 (2009) |
2008 |
31 | EE | Baofeng Guo,
Steve R. Gunn,
Robert I. Damper,
James D. B. Nelson:
Customizing Kernel Functions for SVM-Based Hyperspectral Image Classification.
IEEE Transactions on Image Processing 17(4): 622-629 (2008) |
30 | EE | James D. B. Nelson,
Robert I. Damper,
Steve R. Gunn,
Baofeng Guo:
Signal theory for SVM kernel design with applications to parameter estimation and sequence kernels.
Neurocomputing 72(1-3): 15-22 (2008) |
29 | EE | Baofeng Guo,
Robert I. Damper,
Steve R. Gunn,
James D. B. Nelson:
A fast separability-based feature-selection method for high-dimensional remotely sensed image classification.
Pattern Recognition 41(5): 1653-1662 (2008) |
2007 |
28 | EE | Jianqiang Yang,
Steve R. Gunn:
Exploiting Uncertain Data in Support Vector Classification.
KES (3) 2007: 148-155 |
2006 |
27 | | Craig Saunders,
Marko Grobelnik,
Steve R. Gunn,
John Shawe-Taylor:
Subspace, Latent Structure and Feature Selection, Statistical and Optimization, Perspectives Workshop, SLSFS 2005, Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers
Springer 2006 |
2005 |
26 | EE | Jeremy Rogers,
Steve R. Gunn:
Identifying Feature Relevance Using a Random Forest.
SLSFS 2005: 173-184 |
2004 |
25 | EE | Jeremy Rogers,
Steve R. Gunn:
Ensemble Algorithms for Feature Selection.
Deterministic and Statistical Methods in Machine Learning 2004: 180-198 |
24 | EE | Ahmad Al-Mazeed,
Mark S. Nixon,
Steve R. Gunn:
Classifiers Combination for Improved Motion Segmentation.
ICIAR (2) 2004: 363-371 |
23 | EE | Isabelle Guyon,
Steve R. Gunn,
Asa Ben-Hur,
Gideon Dror:
Result Analysis of the NIPS 2003 Feature Selection Challenge.
NIPS 2004 |
2003 |
22 | EE | Geok See Ng,
Daming Shi,
Steve R. Gunn,
Robert I. Damper:
Nonlinear Active Handwriting Models and Their Applications to Handwritten Chinese Radical Recognition.
ICDAR 2003: 534- |
21 | EE | Daming Shi,
Robert I. Damper,
Steve R. Gunn:
Offline handwritten Chinese character recognition by radical decomposition.
ACM Trans. Asian Lang. Inf. Process. 2(1): 27-48 (2003) |
20 | EE | Daming Shi,
Steve R. Gunn,
Robert I. Damper:
Handwritten Chinese Radical Recognition Using Nonlinear Active Shape Models.
IEEE Trans. Pattern Anal. Mach. Intell. 25(2): 277-280 (2003) |
19 | EE | Daming Shi,
Robert I. Damper,
Steve R. Gunn:
An Approach to Off-Line Handwritten Chinese Character Recognition Based on Hierarchical Radical Decomposition.
Journal of Quantitative Linguistics 10(1): 41-69 (2003) |
18 | EE | Junbin Gao,
Steve R. Gunn,
Chris J. Harris:
Mean field method for the support vector machine regression.
Neurocomputing 50: 391-405 (2003) |
17 | EE | Junbin Gao,
Steve R. Gunn,
Chris J. Harris:
SVM regression through variational methods and its sequential implementation.
Neurocomputing 55(1-2): 151-167 (2003) |
2002 |
16 | EE | Junbin Gao,
Steve R. Gunn,
Jaz S. Kandola:
Adapting Kernels by Variational Approach in SVM.
Australian Joint Conference on Artificial Intelligence 2002: 395-406 |
15 | | Junbin Gao,
Steve R. Gunn,
Chris J. Harris,
Martin Brown:
A Probabilistic Framework for SVM Regression and Error Bar Estimation.
Machine Learning 46(1-3): 71-89 (2002) |
14 | | Steve R. Gunn,
Jaz S. Kandola:
Structural Modelling with Sparse Kernels.
Machine Learning 48(1-3): 137-163 (2002) |
13 | EE | Daming Shi,
Steve R. Gunn,
Robert I. Damper:
Handwritten Chinese character recognition using nonlinear active shape models and the Viterbi algorithm.
Pattern Recognition Letters 23(14): 1853-1862 (2002) |
2001 |
12 | EE | Daming Shi,
Steve R. Gunn,
Robert I. Damper:
A Radical Approach to Handwritten Chinese Character Recognition Using Active Handwriting Models.
CVPR (1) 2001: 670-675 |
11 | EE | Adam I. Wilmer,
Tania Stathaki,
Steve R. Gunn,
Robert I. Damper:
Texture analysis with the Volterra model using conjugate gradient optimisation.
ESANN 2001: 211-216 |
10 | EE | Daming Shi,
Steve R. Gunn,
Robert I. Damper:
Active Radical Modeling for Handwritten Chinese Characters.
ICDAR 2001: 236-240 |
9 | EE | Jun L. Chen,
Steve R. Gunn,
Mark S. Nixon,
Roger N. Gunn:
Markov Random Field Models for Segmentation of PET Images.
IPMI 2001: 468-474 |
8 | | Junbin Gao,
Chris J. Harris,
Steve R. Gunn:
On a Class of Support Vector Kernels Based on Frames in Function Hilbert Spaces.
Neural Computation 13(9): 1975-1994 (2001) |
2000 |
7 | | Robert I. Damper,
Steve R. Gunn,
Mathew O. Gore:
Extracting Phonetic Knowledge from Learning Systems: Perceptrons, Support Vector Machines and Linear Discriminants.
Appl. Intell. 12(1-2): 43-62 (2000) |
1999 |
6 | EE | Steve R. Gunn:
On the discrete representation of the Laplacian of Gaussian.
Pattern Recognition 32(8): 1463-1472 (1999) |
1998 |
5 | | Steve R. Gunn:
Edge Detection Error in the Discrete Laplacian of Gaussian.
ICIP (2) 1998: 515-519 |
4 | EE | Steve R. Gunn,
Mark S. Nixon:
Global and Local Active Contours for Head Boundary Extraction.
International Journal of Computer Vision 30(1): 43-54 (1998) |
1997 |
3 | EE | Steve R. Gunn,
Martin Brown,
Kev M. Bossley:
Network Performance Assessment for Neurofuzzy Data Modelling.
IDA 1997: 313-323 |
2 | EE | Steve R. Gunn,
Mark S. Nixon:
A Robust Snake Implementation; A Dual Active Contour.
IEEE Trans. Pattern Anal. Mach. Intell. 19(1): 63-68 (1997) |
1995 |
1 | | Steve R. Gunn,
Mark S. Nixon:
Improving snake performance via a dual active contour.
CAIP 1995: 600-605 |