Dr. David Windridge


picture of David Windridge
 
            The University of Surrey

Associate Professor/Reader (Middlesex University),
Visting Senior Lecturer (Surrey University)
Centre for Vision Speech and Signal Processing,
School of Electronics and Physical Sciences,
University of Surrey, Guildford GU2 7XH, UK.
  Tel:
  Fax:
  Email:
+44 (0)1483 68-6048
+44 (0)1483 68-6031
d.windridge@mdx.ac.uk Google Scholar link

 





Introduction

I have research interests centred on Machine Learning (in particular kernel methods & classifier decision-fusion) and Cognitive Systems; I also have a historic research interest in Astrophysics/Cosmology, especially stochastic cosmological modelling.

My interest in machine learning has principally focussed on classifier and kernel fusion, for which I have developed a number of approaches including the neutral point substitution method [6] [7] [8], and the tomographic decision fusion analogy [9] [10] (recently kernelised in [11] ). Other methodological arenas include logical rule induction, feature selection and, more recently, quantum computing. Areas of application include computer vision, biometrics and healthcare analytics.

My interest in cognitive systems centres on the notions of cognitive bootstrapping and perception-action learning, firstly, as an appropriate model of human cognition, but also (when implemented appropriately) as a mechanism for machine learning (cf [1], [2], [3]. I have also argued that perception-action learning has the ability to address a number of foundational issues in philosophy (cf [4], [5]).

In pursing the above, I have authored and played a leading role on a number of projects at the interface of machine learning and cognitive systems (including EPSRC ACASVA, EU DIPLECS & DREAMS4CARS), as well as a range of industrial and academic pattern recognition projects, having authored more than 100 publications in the these areas. I am currently an Associate Professor (Reader) in Computer Science at Middlesex University, leading the university's Data Science activity.

Publications

(Preprints can be found at: Google scholar , the University of Surrey preprint server , Researchgate and the Middlesex University preprint archive )

[103] Post-operative pediatric cerebellar mutism syndrome and its association with hypertrophic olivary degeneration
S Avula, M Spiteri, R Kumar, E Lewis, S Harave, D Windridge, C Ong, B Pizer
Quantitative Imaging in Medicine and Surgery 6 (5), 535-544 2016

[102] Quantum Bootstrap Aggregation
D Windridge, R Nagarajan
Proc of 10th international conference on Quantum Interaction (QI 2016), San Francisco

[101] A generalised framework for saliency-based point feature detection
M Brown, D Windridge, JY Guillemaut
Computer Vision and Image Understanding, 2016
http://dx.doi.org/10.1016/j.cviu.2016.09.008

[100] Can DMD obtain a Scene Background in color? (Best paper)
S Tirunagari, N Poh, M Bober, D Windridge
Image, Vision and Computing (ICIVC), International Conference on, 46-50

[99] P. Juneja, P. Evans, D. Windridge, E. Harris
Classification of fibroglandular tissue distribution in the breast based on radiotherapy planning CT
BMC Med Imaging. 2016 Jan 14;16(1):6. doi: 10.1186/s12880-016-0107-2.

[98] M Brown, D Windridge, J-Y Guillemaut
A Generalisable Framework for Saliency-Based Line Segment Detection
Pattern Recognition, Volume 48, Issue 12, December 2015, Pages 39934011

[97] M Spiteri, D Windridge, S Avula, R Kumar, E Lewis
Identifying quantitative imaging features of posterior fossa syndrome in longitudinal MRI
Journal of Medical Imaging, J. Med. Imag. 2(4), 044502 (Oct 23, 2015).
doi:10.1117/1.JMI.2.4.044502

[96] M Brown, D Windridge, JY Guillemaut
Globally Optimal 2D-3D Registration from Points or Lines Without Correspondences
Proceedings of the IEEE International Conference on Computer Vision, 2015, 2111-2119

[95] S Tirunagari, N Poh, M Bober, D Windridge
Windowed DMD as a Microtexture Descriptor for Finger Vein Counter-spoofing in Biometrics
Information Forensics and Security (WIFS), 2015 IEEE International Workshop on, pp 1-6

[94] Windridge, D., Yan, F,
Kernel Combination via Debiased Object Correspondence Analysis,
Information Fusion 03/2015;
DOI:10.1016/j.inffus.2015.02.002

[93] S. Tirungari, N. Poh, D Windridge, A. Ho,
Detection of Face Spoofing Using Visual Dynamics,
IEEE Transactions on Information Forensics and Security 04/2015; 10(4):762-777.
DOI:10.1109/TIFS.2015.2406533

[92] M Spiteri, E Lewis, D Windridge, S Avula,
Longitudinal MRI assessment: The identification of relevant features in the development of Posterior Fossa Syndrome in children,
SPIE Medical imaging 2015, Orlando, Florida; 03/2015,

[91] S Tirunagari, N Poh, G Hu, D Windridge,
Identifying Similar Patients Using Self-Organising Maps: A Case Study on Type-1 Diabetes Self-care Survey Responses,
arXiv preprint arXiv:1503.06316

[90] S Tirunagari, N Poh, H Abdulrahman, N Nemmour, D Windridge,
Breast Cancer Data Analytics With Missing Values: A study on Ethnic, Age and Income Groups,
arXiv preprint arXiv:1503.03680

[89] S Tirunagari, N Poh, K Aliabadi, D Windridge, D Cooke,
Patient level analytics using self-organising maps: A case study on Type-1 Diabetes self-care survey responses, 2014/12/9,
Computational Intelligence and Data Mining (CIDM), 2014 IEEE Symposium on

[88] N Poh, S Tirunagari, D Windridge,
Challenges in designing an online healthcare platform for personalised patient analytics,
2014/12/9, Computational Intelligence in Big Data (CIBD), 2014 IEEE Symposium on

[87] D Windridge,
On the Intrinsic Limits to Representationally-Adaptive Machine-Learning,
arXiv preprint arXiv:1503.02626

[86] Elena Chernousova, Nikolay Razin, Olga Krasotkina, Vadim Mottl, David Windridge,
Linear Regression via Elastic Net: Non-enumerative Leave-One-Out Verification of Feature Selection,
Clusters, Orders, and Trees: Methods and Applications,
Springer Optimization and Its Applications Volume 92, 2014, pp 377-390

[85] Fei Yan, Josef Kittler, David Windridge, William Christmas, Krystian Mikolajczyk, Stephen Cox, Qiang Huang,
Automatic Annotation of Tennis Game: An Integration of Audio, Vision, and Learning,
Image and Vision Computing 11/2014; 32(11).
DOI:10.1016/j.imavis.2014.08.004

[84] Windridge D., Kittler J., De Campos T., Yan F., Christmas W., Khan A.,
Rule Induction for Adaptive Sport Video Characterization Using MLN Clause Templates,
IEEE Multimedia 04/2015; 22(2):24-35. DOI:10.1109/MMUL.2014.36 ·

[83] Da Lio, M; Biral, F; Bertolazzi, E; Galvani, M; Bosetti, P; Windridge, D; Saroldi, A; Tango, F,
Artificial Co-Drivers as a Universal Enabling Technology for Future Intelligent Vehicles and Transportation Systems,
IEEE Transactions on Intelligent Transportation Systems and Intelligent Transportation Systems Magazine, 2014, 16(1):244-263. DOI:10.1109/TITS.2014.2330199

[82] E Chernousova, P Levdik, A Tatarchuk, V Mottl, D Windridge
Hypothetical Cross Validation for the Choice of Structural Parameters in Feature-Selective Support Vector Machines
In Proc. 22nd International Conference on Pattern Recognition (ICPR 2014), 2014.

[81] Windridge D.; Bober M.
A Kernel-Based Framework for Medical Big-Data Analytics,
in Interactive Knowledge Discovery and Data Mining in Biomedical Informatics,
Lecture Notes in Computer Science Vol. 8401, 2014, doi: 10.1007/978-3-662-43968-5_11

[80] A Tatarchuk, V Sulimova, V Mottl, D Windridge
Supervised Selective Kernel Fusion for Membrane Protein Prediction
In Proc. of the 9th IAPR conference on Pattern Recognition in Bioinformatics (PRIB 2014), 2014

[79] M. Brown, J.-Y. Guillemaut and D Windridge.
A Saliency-based Framework for 2D-3D Registration.
In Proc. International Conference on Computer Vision Theory and Applications (VISAPP 2014), 2014.

[78] Khan, A. ; Windridge, D. ; Kittler, J.
A Multilevel Chinese Takeaway Process and Label-Based Processes for Rule Induction in the Context of
Automated Sports Video Annotation
IEEE Transactions on Cybernetics 2014 Digital Object Identifier: 10.1109/TCYB.2014.2299955
(formerly IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS Part B)

[77] Kittler J, Christmas WJ, de Campos TE, Windridge D, Yan F, Illingworth J, Osman M,
Domain anomaly detection in machine perception: A system architecture and taxonomy,
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2014 ISSN: 0162-8828,
Digital Object Identifier : 10.1109/TPAMI.2013.209

[76] Hope C, Sterr A, Elangovan P, Geades N, Windridge D, Wells K, Young K,
High throughput screening for mammography using a human-computer interface with Rapid Serial Visual Presentation (RSVP)
Proceedings of SPIE - The International Society for Optical Engineering 8673 2013

[75] Taya S, Windridge D, Osman M,
Trained eyes: experience promotes adaptive gaze control in dynamic and uncertain visual environments.
PLoS One 8(8):e71371 2013

[74] Teofilo De Campos, Aftab Khan, Fei Yan, Nazli Farajidavar, David Windridge, Josef Kittler and William Christmas,
A framework for automatic sports video annotation with anomaly detection and transfer learning,
MLCOGS 2013

[73] O Seredin, V Mottl, A Tatarchuk, N Razin, D Windridge,
Convex Support and Relevance Vector Machines for Selective Multimodal Pattern Recognition,
ICPR 2012

[72] A Shaukat, A Gilbert, D Windridge, R Bowden,
A Top-down and Bottom-up Approach to Detect Pedestrians,
ICPR 2012

[71] F Yan, J Kittler, K Mikolajczyk, D Windridge,
Automatic Annotation of Court Games with Structured Output Learning,
ICPR 2012

[70] S Kiani, Wells K, Windridge D, Gordon, I,
On-Line Spatio-Temporal Independent Component Analysis for Motion Correction in Renal DCE-MRI,
2012 IEEE MIC Anaheim, CA.

[69] N. Razin, D. Sungurov, V. Mottl, I. Torshin, V. Sulimova, O. Seredin, D. Windridge,
Application of the Multi-modal Relevance Vector Machine to the problem of protein secondary structure prediction,
PRIB 2012.

[68] Goswami D, Chan CH, Windridge D, Kittler J,
Evaluation of face recognition system in heterogeneous environments (visible vs NIR),
Proceedings of the IEEE International Conference on Computer Vision. 2160-2167. 2011 DOI

[67] D Windridge, A Shaukat, E Hollnagel,
Characterizing Driver Intention via Hierarchical Perception Action Modeling,
IEEE Transactions on Human-Machine Systems 43(1):17-31 25 Oct 2012
(formerly IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS Part A)

[66] D Windridge, M Felsberg, A Shaukat,
A Framework for Hierarchical Perception-Action Learning Utilizing First Logic Resolution,
IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS Part B, DOI: 10.1109/TSMCB.2012.2202109

[65] Looking to Score: The Dissociation of Goal Influence on Eye Movement and Meta-attentional Allocation in
A Complex Dynamic Natural Scene,
Taya S, Windridge D, Osman M,
PLoS ONE 2012

[64] The effects of goal-oriented task on eye-movements during dynamic natural scene observation,
Taya S, Windridge D, Kittler J, Osman M,
Journal of Vision (J Vis), September 23, 2011 11(11): 477; doi:10.1167/11.11.477

[63] Cross Spectral Face Recognition between Near Infrared and Visible Faces,
Goswami D., Windridge D., Chan CH, Kittler J,
Proc. of the 3rd British Machine Vision UK Student Workshop (BMVC'11 WS, Dundee, Scotland, 2nd September, 2011)

[62] Q Huang and S Cox and F Yan and T E deCampos and D Windridge and J Kittler and W Christmas,
Improved Detection of Ball Hit Events in a Tennis Game Using Multimodal Information,
In 11th International Conference on Auditory-Visual Speech Processing (AVSP), 2011

[61] T deCampos and M Barnard and K Mikolajczyk and J Kittler and F Yan and W Christmas and D Windridge,
An evaluation of bags-of-words and spatio-temporal shapes for action recognition ,
In IEEE Workshop on Applications of Computer Vision (WACV), 2011

[60] N FarajiDavar and T E deCampos and D Windridge and J Kittler and W Christmas,
Domain Adaptation in the Context of Sport Video Action Recognition,
In Domain Adaptation Workshop, in conjunction with NIPS, 2011

[59] Maxim Panov, Alexander Tatarchuk, Vadim Mottl, and David Windridge,
A Modified Neutral Point Method for Kernel-Based Fusion of Pattern-Recognition Modalities with Incomplete Data Sets
9th International Workshop on Multiple Classifier Systems, MCS 2011, 2011

[58] Rule-based modulation of visual attention allocation,
Taya S, Windridge D, Kittler J, Osman M,
Perception 39 ECVP Supplement, page 81, 2010

[57] Shuichiro Taya and David Windridge and Josef Kittler and Magda Osman,
Investigating the Influence of Task-Specic Goals on Attention Allocation and Eye Movement Behavior
While Viewing a Dynamic Scene,
In 51st Annual Meeting of the Psychonomic Society, 2010

[56] I Almajai, F Yan, T de Campos, A Khan, W Christmas, D Windridge and J Kittler,
Anomaly Detection and Knowledge Transfer in Automatic Sports Video Annotation
In Proceedings of DIRAC Workshop, European Conference on Machine Learning and
Principles and Practice of Knowledge Discovery in Databases
In Proc. of ECML PKDD 2010, 2010

[55] I Almajai and J Kittler and T DeCampos and W. Christmas and F Yan and D Windridge and A Khan,
Ball Event Recognition using HMM for Automatic Tennis Annotation,
In Proceedings of Intl. Conf. on Image Proc., 2010

[54] Aftab Khan and David Windridge and Teofilo de Campos and Josef Kittler and William Christmas,
Lattice-based Anomaly Rectification for Sport Video Annotation
In Proceedings of ICPR 2010, 2010

[53] N. Poh and D. Windridge and V. Mottl and A. Tatarchuk and A. Eliseyev,
Addressing Missing Values in Kernel-based Multimodal Biometric Fusion using Neutral Point Substitution
In IEEE Trans. on Information Forensics and Security, 2010

[52] I Almajai and J Kittler and T DeCampos and W. Christmas and F Yan and D Windridge and A Khan,
Ball Event Recognition Using HMMs For Automatic Tennis Annotation
In Proceedings of Intl. Conf. on Image Proc., 2010

[51] Affan Shaukat and David Windridge and Erik Hollnagel and Luigi Macchi,
Adaptive, Perception-Action-based Cognitive Modelling of Human Driving Behaviour
Using Control, Gaze and Signal Inputs
In Proceedings of Brain Inspired Cognitive Systems 2010 (BICS 2010), 2010

[50] Affan Shaukat and David Windridge and Erik Hollnagel and Luigi Macchi,
Induction of the Human Perception-Action Hierarchy Employed in Junction-Navigation Scenarios
In Proc. of 4th International Conference on Cognitive Systems, CogSys 2010,
ETH Zurich. Switzerland, January 27 - 28, 2010, 2010

[49] Alexander Tatarchuk and Eugene Urlov and Vadim Mottl and David Windridge,
A Support Kernel Machine for Supervised Selective Combining of Diverse Pattern-Recognition Modalities
In Proc. Multiple Classifier Systems, 9th International Workshop, MCS 2010, 2010

[48] D Windridge and J Kittler,
Perception-Action Learning as an Epistemologically-Consistent Model for Self-Updating Cognitive Representation
In Advances in Experimental Medicine and Biology, 2010;657:95-134.

[47] M Felsberg and A Shaukat and D Windridge,
Online Learning in Perception-Action Systems
In Proceedings of ECCV 2010 Workshop on Vision for Cognitive Tasks,
11th European Conference on Computer Vision (ECCV 2010), Crete, Greece, 2010

[46] David Windridge,
Tomographic Considerations in Ensemble Bias/Variance Decomposition
In Proc. Multiple Classifier Systems, 9th International Workshop, MCS 2010, 2010

[45] Alexander Tatarchuk, Valentina Sulimova, David Windridge, Vadim Mottl,
Supervised Selective Combining Pattern Recognition Modalities and its Application to Signature Verification
by Fusing On-Line and Off-Line Kernels,
8th International Workshop on Multiple Classifier Systems MCS 2009, Reykjavik, 2009.

[44] D. Windridge, N. Poh, V. Mottl, A. Tatarchuk, A. Eliseyev,
Handling Multimodal Information Fusion with Missing Observations Using the Neutral Point Substitution Method,
8th International Workshop on Multiple Classifier Systems MCS 2009, Reykjavik, 2009.

[43] Mikhail Shevchenko, David Windridge and Josef Kittler,
A Linear-Complexity Reparametrisation Strategy for the Hierarchical Bootstrapping of Capabilities
within Percept-Action Architectures,
Image and Vision Computing, 27, 2009, pp 1702-1714

[42] D. Windridge, V. Mottl, A. Tatarchuk, A. Eliseyev,
Selectivity Supervision in Combining Pattern-Recognition Modalities
by Feature- and Kernel-Selective Support Vector Machines
Proc. 19th International Conference of Pattern Recognition, ICPR 2008, Florida, USA

[41] David Windridge, Debaditya Goswami, Josef Kittler,
Subsurface Scattering Deconvolution for Improved NIR-Visible Facial Image Correlation,
Proc. of 8th IEEE International Conference on Automatic Face and Gesture Recognition, 2008

[40] David Windridge, Josef Kittler,
A model for empirical validation in self-updating cognitive representation,
Proceedings of Brain Inspired Cognitive Systems 2008 (BICS 2008), Sao Luis, Brazil, 2008

[39] David Windridge, Mikhail Shevchenko, Josef Kittler
An Entropy-Based Approach to the Hierarchical Acquisition of Perception- Action Capabilities
Proc. of 4th International Cognitive Vision Workshop ICVW 2008,
(6th International Conference on Computer Vision Systems ICVS 2008), Santorini, Greece, 2008

[38] Article relating to the DIPLECS project arising from an interview I gave to the The Engineer magazine: link

[37] D. Windridge and Josef Kittler,
Epistemic Constraints on Autonomous Symbolic Representation in Natural and Artificial Agents,
Applications of Computational Intelligence in Biology: Current Trends and Open Problems,
Studies in Computational Intelligence (SCI),
vol(122), 2008, Springer, ISBN: 978-3-540-78533-0

[36] D. Windridge, V. Mottl, A. Tatarchuk. and A Eliseyev,
The Neutral Point Method for Kernel-Based Combination of Disjoint Training in Multi-Modal Pattern Recognition,
Proceedings of the 7th International Workshop on Multiple Classifier Systems, May, 2007, Springer

[35] D Windridge and J Kittler,
Open-Ended Inference of Relational Representations in the COSPAL Perception-Action Architecture,
Proc. of International Cognitive Vision Workshop (ICVW 2007),
part of 5th International Conference on Computer Vision Systems (ICVS 2007), 2007, Springer

[34] D Windridge, R Patenall and J Kittler,
Factoriality as an Indicator of Stochastic Vector Quantiser Generalising Ability,
CVSSP Technical Report VSSP-TR-5/2007, University of Surrey, UK, 2007

[33] D. Windridge, V. Mottl, A. Tatarchuk. and A Eliseyev,
The Relationship Between Kernel And Classifier Fusion In Kernel-Based Multi-Modal Pattern Recognition:
An Experimental Study,
Proceedings of the International Conference on Machine Learning and Cybernetics 2007 (ICMLC 2007),
August, 2007, Hong Kong, China

[32] J Kittler, M Shevchenko and D Windridge,
Visual Bootstrapping for Unsupervised Symbol Grounding,
Proceedings of 8th Advanced Concepts for Intelligent Vision Systems International Conference, September, 2006,
Springer, eds. J Blanc-Talon and W Philips and D Popescu and P Scheunders, pp 1037-1046

[31] J Kittler, M Shevchenko and D Windridge,
Cognitive Learning with Automatic Goal Acquisition,
Frontiers in Artificial Intelligence and Applications - Third Standing AI Researcher's Symposium, 2006,,
IOS Press, August, eds. L Penserini and P Peppas and A Perini, vol 142, isbn 978-1-58603-645-4.

[30] Bowden R, Ellis L, Kittler J, Shevchenko M, Windridge D.,
Unsupervised Symbol Grounding and Cognitive Bootstrapping in Cognitive Vision,
(Lecture Notes in Computer Science, Vol. 3617, Sept 2005)

[29] D Windridge,
Cognitive Bootstrapping: A Survey of Bootstrap Mechanisms for Emergent Cognition,
CVSSP Technical Report VSSP-TR-2/2005, University of Surrey, UK, 2005. ISBN: 978-1-84469-026-8 pdf

[28] Josef Kittler, William J. Christmas, Alexey Kostin, F. Yan, Ilias Kolonias, David Windridge,
A Memory Architecture and Contextual Reasoning Framework for Cognitive Vision,
(Lecture Notes in Computer Science, Vol. 3540, June 2005)

[27] David Windridge,
Morphologically Debiased Classifier Fusion: A Tomography-Theoretic Approach,
Advances in Imaging and Electron Physics, vol 134, 2005, Elsevier Academic Press

[26] D. Windridge, R. Bowden,
Hidden Markov chain estimation and parameterisation via ICA-based feature-selection,
Pattern Analysis & Applications, July 2005, vol. 8, pp 115-124,
Publisher: Springer-Verlag London Ltd

[25] David Windridge, Josef Kittler,
Performance Measures of the Tomographic Classifier Fusion Methodology,
Intern. Jrnl. of Pattern Recognition and Artificial Intelligence, Vol. 19 Number 6, 2005

[24] Robin Patenall, David Windridge, Josef Kittler,
Multiple Classifier Fusion Performance in Networked Stochastic Vector Quantisers
Lecture Notes in Computer Science, Vol. 3541, p. 128, June 2005

[23] David Windridge, Robin Patenall, Josef Kittler,
The Relationship Between Classifier Factorisation and Performance
in Stochastic Vector Quantisation
(Lecture Notes in Computer Science, Vol. 3077, June 2004)

[22] D. Windridge, R. Bowden,
Induced Decision Fusion in Automated Sign Language Interpretation:
Using ICA to Isolate the Underlying Components of Sign
(Lecture Notes in Computer Science, Vol. 3077, June 2004)

[21] D. Windridge, R. Bowden, Josef Kittler,
A General Strategy for Hidden Markov Chain Parameterisation in
Composite Feature-Spaces
(Lecture Notes in Computer Science, Vol. 3138, August 2004)

[20] Richard Bowden, David Windridge, Timor Kadir, Andrew Zisserman, Michael Brady,
A Linguistic Feature Vector for the Visual Interpretation of Sign Language,
European Conference on Computer Vision 2004,
(Lecture Notes in Computer Science, Vol. 3024, pp390)

[19] D. Windridge,
On the Generalisation of Gaussian Mixture Model HMM Parameterisation Techniques,
(Univ. of Surrey Technical Report: VSSP-TR-1/2004), UNIS, UK

[18] D. Windridge, Josef Kittler,
A Morphologically Optimal Strategy for Classifier Combination,
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,
Vol 25, no. 3, March 2003, pp. 343-353

[17] D. Windridge,
Economic Tomographic Classifier Fusion: Eliminating Redundant H gbom Deconvolution Cycles
in the Sum-Rule Domain
(Univ. of Surrey Technical Report: VSSP-TR-1/2003)

[16] D. Windridge, Josef Kittler,
The Practical Performance Characteristics of Tomographically Filtered Multiple Classifier Fusion,
4th International Workshop on Multiple Classifier Systems, 2003,
(LNCS. Vol. 2709, pp. 166 - 175, June 2003)

[15] Josef Kittler, Alireza Ahmadyfard, David Windridge,
Serial Multiple Classifier Systems Exploiting a Coarse to Fine Output Coding,
4th International Workshop on Multiple Classifier Systems, 2003,
(LNCS. Vol. 2709, pp. 106 - 114, June 2003)

[14] D. Windridge,Josef Kittler,
Morphologically Unbiased Classifier Combination Through Graphical PDF Correlation,
LNCS 2396, August 2002

[13] D. Windridge,Josef Kittler,
On the General Application of the Tomographic Classifier Fusion Methodology,
LNCS. Vol. 2364, June 2002

[12] Kittler J, Yusoff Y, Christmas W, Windeatt T, Windridge D,
Boosting Multiple Experts by Joint Optimisation of Decision Thresholds,
Pattern Recognition and Image Analysis 11(3), 2001, pp 529-541.

[11] D. Windridge,Josef Kittler,
Classifier Combination as a Tomographic Process,
(Multiple Classifier Systems, LNCS. Vol. 2096 , 2001.)

[10] D. Windridge, S. Phillipps,
A Fluctuation Analysis for Optical Cluster Galaxies - I Theory,
MNRAS (Mon. Not. Roy. Astron. Soc), 319, p. 591, 11/2000

[9] D. Windridge,Josef Kittler,
Combined Classifier Optimisation via Feature Selection,
Advances in Pattern Recognition, LNCS. Vol. 1876, August 2000.

[8] D. Windridge,
A Generalised Solution to the Problem of Multiple Expert Fusion.
(Univ. of Surrey Technical Report: VSSP-TR-5/2000)

[7] D. Windridge,
A Fluctuation Analysis for Optical Cluster Galaxies, Ph.D. Thesis, University of Bristol, 1999

[6] Groot, P. J.; Galama, T. J.; Vreeswijk, P. M.; Wijers, R. A. M. J.; Pian, E.; Palazzi, E.; van Paradijs,
J.; Kouveliotou, C.; in 't Zand, J. J. M.; Heise, J.; Robinson, C.; Tanvir, N.; Lidman, C.; Tinney, C.;
Keane, M.; Briggs, M.; Hurley, K.; Gonzalez, J.-F.; Hall, P.; Smith, M. G.; Covarrubias, R.; Jonker, P.; Casares, J.;
Frontera, F.; Feroci, M.; Piro, L.; Costa, E.; Smith, R.; Jones, B.; Windridge, D.; Bland-Hawthorn, J.; Veilleux, S.;
Garcia, M.; Brown, W. R.; Stanek, K. Z.; Castro-Tirado, A. J.; Gorosabel, J.; Greiner, J.; Jaeger, K.; Bohm, A. B.;
Fricke, K. J.
The Rapid Decay of the Optical Emission from GRB 980326 and Its Possible Implications,
Astrophysical Journal v.502, August 1998, p.L123 08/1998

[5] Cruikshank, D. P.; Gladman, B.; Smith, R. M.; Jones, J. B.; Windridge, D.; Hall, P.; Graham, D.; Kavelaars, J. J.;
Williams, G. V.; Aksnes, K.; Marsden, B. G.
S/1997 U 1: Precovery and recovery observations of this satellite are reported:
Circular of the Int. Astron. Union., 6870, 1 (1998). 04/1998

[4] Smith, R. M.; Jones, J. B.; Windridge, D.; Gladman, B.; Hall, P.; Graham, D.; Kavelaars, J. J.;
Williams, G. V.; Aksnes, K.; Marsden, B. G.
S/1997 U 2: The recovery of the brighter of the new Uranian satellites is reported
Circular of the Int. Astron. Union., 6869, 1 (1998). 04/1998

[3] Windridge, D.; Phillipps, S.; Birkinshaw, M.
Measures of Galactic and Intergalactic Mass in Clusters.
(P.A.S.P. Proceedings of I.A.U. Symp. No. 179. 1997)

[2] Windridge, D.; Phillipps, S.
The Baryonic and Dark Matter Contribution to Cluster Masses by Dwarf Galaxies.
(Proceedings of Astronomical Society of the Pacific, July 1996, p. 329-334.)

[1] Windridge, D, MERLIN observation of the gravitational lens system MG0414+0534, 1996, Research Report,
University of Manchester (Nuffield Radio Astronomy Laboratories)


last updated 10/2016