Dr. David Windridge is Associate Professor in Computer Science at Middlesex and heads the University's Data Science activities. His research interests center on the fields of machine-learning (A.I.), cognitive systems, quantum computing and computer vision (he also has a former research interest in astrophysics, having obtained his Ph.D. in Cosmology at the University of Bristol).
He has authored and played a leading role on a number of large-scale machine-learning projects in academic and industrial research settings (including the EU DREAMS4CARS, EPSRC ACASVA and EU DIPLECS projects). He is also interested in cross-over areas of data science and has won a number of interdisciplinary research grants in areas as diverse as psychological modelling and proteomic classification. He is a Visiting Professor at Trento University, Italy, and a visiting Senior Lecturer at the University of Surrey. He has authored more than 100 peer-reviewed publications.
Journal Papers:
[125] David Windridge and Serge Thill,
Representational Fluidity in Embodied (Artificial) Cognition,
BioSystems, 172, 9-17, 2018
[124] David Windridge, Riccardo Mengoni, Raja Nagarajan, Alessandra di Pierro (Accepted/In Press)
Quantum Error Correcting Output Codes
International Journal of Quantum Information, Vol. 16, No. 08 , 2018
doi.org/10.1142/S0219749918400038
[123] S Juddoo, C George, P Duquenoy, D Windridge
Data governance in the health industry: investigating data quality dimensions within a big data context,
Applied System Innovation 1 (4), 43, 2018
[122] Avula, S., Spiteri, M., Guillemaut, J. Y., Windridge, D., Kumar, R., Pizer, B., ... & Lewis, E. (2018).
Neuro-Oncology,
Volume 20, Issue suppl_2, 22 June 2018, Pages i171, https://doi.org/10.1093/neuonc/noy059.647
[121] C Spanos, EM Maldonado, CP Fisher, P Leenutaphong, E Oviedo-Orta, David Windridge, Francisco J Salguero, Alexandra Bermúdez-Fajardo, Mark E Weeks, Caroline Evans, Bernard M Corfe, Naila Rabbani, Paul J Thornalley, Michael H Miller, Huan Wang, John F Dillon, Alberto Quaglia, Anil Dhawan, Emer Fitzpatrick, J Bernadette Moore,
Correction: to: Proteomic identification and characterization of hepatic glyoxalase 1 dysregulation in non-alcoholic fatty liver disease
Proteome science 16 (1), 13, 2018
[120] C Spanos, EM Maldonado, CP Fisher, P Leenutaphong, E Oviedo-Orta, David Windridge, Francisco J Salguero, Alexandra Bermúdez-Fajardo, Mark E Weeks, Caroline Evans, Bernard M Corfe, Naila Rabbani, Paul J Thornalley, Michael H Miller, Huan Wang, John F Dillon, Alberto Quaglia, Anil Dhawan, Emer Fitzpatrick, J Bernadette Moore,
Proteomic identification and characterization of hepatic glyoxalase 1 dysregulation in non-alcoholic fatty liver disease
Proteome science 16 (1), 4, 2018
[119] K Bhattacharjee, S Kumar, HM Pandey, M Pant, D Windridge,
An improved block matching algorithm for motion estimation in video sequences and application in robotics
Computers & Electrical Engineering 68, 92-106, 2018
[118] D Windridge
Emergent Intentionality in Perception-Action subsumption Hierarchies
Frontiers in Robotics and AI 4, 38, 1, 2017
[117] S Tirunagari, N Poh, K Wells, M Bober, I Gorden, D Windridge,
Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition, Machine Vision and Applications
May 2017, Volume 28, Issue 3, pp 393–407 28: 393. doi:10.1007/s00138-017-0835-5
[116] M. Brown, D. Windridge, J-Y Guillemaut,
A Generalised Framework for Saliency-Based Point Feature Detection,
Computer Vision and Image Understanding , 117-137, 4, 2016
http://dx.doi.org/10.1016/j.cviu.2016.09.008
[115] S Avula, M Spiteri, R Kumar, E Lewis, S Harave, D Windridge, C Ong, B Pizer
Post-operative pediatric cerebellar mutism syndrome and its association with hypertrophic olivary degeneration
Quantitative Imaging in Medicine and Surgery 6 (5), 535-544, 2016 doi: 10.21037/qims.2016.10.11
[114] 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.
[113] 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 3993–4011
[112] 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
[111] Windridge, D., Yan, F,
Kernel Combination via Debiased Object Correspondence Analysis,
Information Fusion 03/2015;
DOI:10.1016/j.inffus.2015.02.002
[110] 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
[109] 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
[108] Windridge D., Kittler J., De Campos T., Yan F., Christmas W., Khan A.,
A Novel Markov Logic Rule Induction Strategy for Characterizing Sports Video Footage,
IEEE Multimedia 04/2015; 22(2):24-35. DOI:10.1109/MMUL.2014.36 ·
[107] 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
[106] 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
[105] 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)
[104] 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
[103] 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
[102] 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)
[101] 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
[100] 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 7 (6), 2012, e39060
[99] 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
[98] Rule-based modulation of visual attention allocation,
Taya S, Windridge D, Kittler J, Osman M,
Perception 39 ECVP Supplement, page 81, 2010
[97] N. Poh, D. Windridge, V. Mottl, A. Tatarchuk, A. Eliseyev,
Addressing Missing Values in Kernel-based Multimodal Biometric Fusion using Neutral Point Substitution
Information Forensics and Security, IEEE Transactions on 5 (3), 461-469
[96] D Windridge, 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.
[95] Mikhail Shevchenko, David Windridge, Josef Kittler,
A Linear-Complexity Reparametrisation Strategy for the Hierarchical Bootstrapping of Capabilities
within Perception-Action Architectures,
Image and Vision Computing, 27, 2009, pp 1702-1714
[94] David Windridge,
Morphologically Debiased Classifier Fusion: A Tomography-Theoretic Approach,
Advances in Imaging and Electron Physics, vol 134, 2005, Elsevier Academic Press
[93] 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
[92] 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
[91] D. Windridge, Josef Kittler,
A morphologically optimal strategy for classifier combination: Multiple expert fusion as a tomographic process
Pattern Analysis and Machine Intelligence, IEEE Transactions on 25 (3), 343-353
[90] 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.
[89] D. Windridge, S. Phillipps,
A Fluctuation Analysis for Optical Cluster Galaxies - I Theory,
MNRAS (Mon. Not. Roy. Astron. Soc), 319, p. 591, 11/2000
[88] 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
[87] 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
[86] 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
Peer-Reviewed Book Chapters:
[85] 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
[84] D. Windridge, 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
[83] Josef Kittler, William J. Christmas, Alexey Kostin, F. Yan, Ilias Kolonias, David Windridge,
A Memory Architecture and Contextual Reasoning Framework for Cognitive Vision,
Image Analysis, 343-358
(Lecture Notes in Computer Science, Vol. 3540, June 2005)
Conference Papers:
[82] David Windridge, Florian Kammueller (in press)
Edit Distance Kernelization of NP Theorem Proving for Polynomial-Time Machine Learning of Proof Heuristics,
Proc. of Future of Information and Communications Conference (IEEE FICC), 14-15 March 2019, San Francisco, Springer Lecture Notes in Networks and Systems
[81] Hari Mohan Pandey, David Windridge
A genetic deep learning model for electrophysiological soft robotics
In: 8th International Workshop on Soft Computing , Application, 13-15 Sept 2018, University of Arad, Romania. (Accepted/In press)
[80] HM Pandey, D Windridge
A comprehensive classification of deep learning libraries
International Congress on Information and Communication Technology, 27-28 Feb 2018, London, UK. (Accepted/In press), Springer, 2018
[79] A Di Pierro, R Mengoni, R Nagarajan, D Windridge
Hamming distance kernelisation via topological quantum computation
International Conference on Theory and Practice of Natural Computing, 269-280, 2017
[78] Exploiting dream-like simulation mechanisms to develop safer agents for automated driving: The “Dreams4Cars” EU research and innovation action
M Da Lio, A Mazzalai, D Windridge, S Thill, H Svensson, M Yüksel, Kevin Gurney, Andrea Saroldi, Luisa Andreone, Sean R Anderson, Hermann-Josef Heich,
Intelligent Transportation Systems (ITSC), 2017 IEEE 20th International Conference on, pp 1-6, 2017
[77] Attfield S, Hewitt D, Xu K, Passmore P J, Wagstaff A, Phillips G, Windridge D, Dash G, Chapman R, Mason L,
Addressing VAST 2016 mini challenge 2 with POLAR kermode, classifier, excel on a power wall and data timelines. In: IEEE VAST Challenge 2016, 23 Oct 2016, Baltimore, MD, USA.
[76] D. Windridge, R. Nagarajan,
Quantum Bootstrap Aggregation,
Quantum Interaction (QI 2016),San Francisco State University (SFSU), 2016
[75] Turki Aljrees, Daming Shi, David Windridge, William Wong (2016),
Criminal pattern identification based on modified K-means clustering, Machine Learning and Cybernetics (ICMLC),
2016 International Conference on, Vol 2 pp. 799-806
[74] Can DMD obtain a Scene Background in color? (Best paper award)
S Tirunagari, N Poh, M Bober, D Windridge
Image, Vision and Computing (ICIVC), International Conference on, 46-50
[73] 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
[72] 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
[71] Non-enumerative Cross Validation for the Determination of Structural Parameters in Feature-Selective SVMs,
E Chernousova, P Levdik, A Tatarchuk, V Mottl, D Windridge
Pattern Recognition (ICPR), 2014 22nd International Conference on, 3654-3659
[70] M Spiteri, E Lewis, D Windridge, S Avula,
Logitudinal MRI assessment: The identification of relevant features in the development of Posterior Fossa Syndrome in children,
SPIE Medical imaging 2015, Orlando, Florida; 03/2015
[69] 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
[68] 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
[67] 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.
[66] 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
[65] 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.
[64] 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
[63] 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,
Proceedings of Machine Learning and Cognitive Science (MLCOGS), Palma de Mallorca, 2013
[62] O Seredin, V Mottl, A Tatarchuk, N Razin, D Windridge,
Convex Support and Relevance Vector Machines for Selective Multimodal Pattern Recognition,
Pattern Recognition (ICPR), 2012 21st International Conference on, 1647-1650
[61] A Shaukat, A Gilbert, D Windridge, R Bowden,
Meeting in the Middle: A top-down and bottom-up approach to detect pedestrians
Pattern Recognition (ICPR), 2012 21st International Conference on, 874-877
[60] F Yan, J Kittler, K Mikolajczyk, D Windridge,
Automatic Annotation of Court Games with Structured Output Learning,
In Proc. International Conference on Pattern Recognition, ICPR 2012
[59] S Kiani, Wells K, Windridge D, Gordon I,
On-Line Spatio-Temporal Independent Component Analysis for Motion Correction in Renal DCE-MRI,
Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), IEEE MIC Anaheim, CA., 2012
[58] 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,
Pattern Recognition in Bioinformatics, 153-165, 2012.
[57] 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
[56] 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)
[55] 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
[53] T deCampos, M Barnard, K Mikolajczyk, J Kittler, F Yan, W Christmas, D Windridge,
An evaluation of bags-of-words and spatio-temporal shapes for action recognition ,
In IEEE Workshop on Applications of Computer Vision (WACV), 344-351, 2011
[53] 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
[52] 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, 126-136, 2011
[51] Shuichiro Taya, David Windridge, Josef Kittler, 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
[50] 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
[49] 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,
Image Processing (ICIP), 2010 17th IEEE International Conference on, 1509-1512 2010
[48] A Khan, D Windridge, T de Campos, J Kittler, W Christmas
Lattice-based anomaly rectification for sport video annotation
Pattern Recognition (ICPR), 2010 20th International Conference on, 4372-4375
[47] I Almajai, J Kittler, T DeCampos, W. Christmas, F Yan, D Windridge, A Khan,
Ball Event Recognition Using HMMs For Automatic Tennis Annotation
In Proceedings of Intl. Conf. on Image Proc., 2010
[46] Affan Shaukat, David Windridge, Erik Hollnagel, 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
[45] A Shaukat, D Windridge, E Hollnagel, L Macchi, J Kittler,
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
[44] A Tatarchuk, E Urlov, V Mottl, D 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
[43] M Felsberg, A Shaukat, 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
[42] David Windridge,
Tomographic Considerations in Ensemble Bias/Variance Decomposition
In Proc. Multiple Classifier Systems, 9th International Workshop, MCS 2010, 2010
[41] 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.
[40] 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.
[39] 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
[38] D Goswami, J Kittler, D Windridge,
Subsurface Scattering Deconvolution for Improved NIR-Visible Facial Image Correlation,
Proc. of 8th IEEE International Conference on Automatic Face and Gesture Recognition, 2008
[37] 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
[36] D Windridge, M Shevchenko, J 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
[35] D. Windridge, V. Mottl, A. Tatarchuk., 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
[34] D Windridge, 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
[33] D. Windridge, V. Mottl, A. Tatarchuk., 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, 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, 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] 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
[28] David Windridge, Robin Patenall, Josef Kittler,
The Relationship Between Classifier Factorisation and Performance
in Stochastic Vector Quantisation
Multiple Classifier Systems, 194-203
(Lecture Notes in Computer Science, Vol. 3077, June 2004)
[27] D. Windridge, R. Bowden,
Induced Decision Fusion in Automated Sign Language Interpretation:
Using ICA to Isolate the Underlying Components of Sign
Multiple Classifier Systems, 303-313
(Lecture Notes in Computer Science, Vol. 3077, June 2004)
[26] D. Windridge, R. Bowden, Josef Kittler,
A General Strategy for Hidden Markov Chain Parameterisation in
Composite Feature-Spaces
Structural, Syntactic, and Statistical Pattern Recognition, 1069-1077
(Lecture Notes in Computer Science, Vol. 3138, August 2004)
[25] 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)
[24] 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)
[23] 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)
[22] D. Windridge,Josef Kittler,
Morphologically Unbiased Classifier Combination Through Graphical PDF Correlation,
Structural, Syntactic, and Statistical Pattern Recognition, 789-797
LNCS 2396, August 2002
[21] D. Windridge,Josef Kittler,
On the General Application of the Tomographic Classifier Fusion Methodology,
Multiple Classifier Systems, 149-158
LNCS. Vol. 2364, June 2002
[20] D. Windridge,Josef Kittler,
Classifier Combination as a Tomographic Process,
(Multiple Classifier Systems, LNCS. Vol. 2096 , 2001.)
[19] D. Windridge,Josef Kittler,
Combined Classifier Optimisation via Feature Selection,
Advances in Pattern Recognition, LNCS. Vol. 1876, August 2000.
[18] Windridge, D.; Phillipps, S.; Birkinshaw, M.
Measures of Galactic and Intergalactic Mass in Clusters.
New Horizons from Multi-Wavelength Sky Surveys: Proceedings of I.A.U. Symp. No. 179. 1997
[17] 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.
Technical Reports:
[16] S Tirunagari, S Kouchaki, N Poh, M Bober, D Windridge
Dynamic Mode Decomposition for Univariate Time Series: Analysing Trends and Forecasting
HAL Id: hal-01463744, https://hal.archives-ouvertes.fr/hal-01463744, 2017
[15] 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
[14] 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
[13] D Windridge,
On the Intrinsic Limits to Representationally-Adaptive Machine-Learning,
arXiv preprint arXiv:1503.02626
[12] D Windridge, R Patenall, J Kittler,
Factoriality as an Indicator of Stochastic Vector Quantiser Generalising Ability,
CVSSP Technical Report VSSP-TR-5/2007, University of Surrey, UK, 2007
[11] 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
[10] D. Windridge,
On the Generalisation of Gaussian Mixture Model HMM Parameterisation Techniques,
(Univ. of Surrey Technical Report: VSSP-TR-1/2004), UNIS, UK
[9] D. Windridge,
A Generalised Solution to the Problem of Multiple Expert Fusion.
(Univ. of Surrey Technical Report: VSSP-TR-5/2000)
[8] D. Windridge,
Economic Tomographic Classifier Fusion: Eliminating Redundant Högbom Deconvolution Cycles
in the Sum-Rule Domain
(Univ. of Surrey Technical Report: VSSP-TR-1/2003)
Other:
[7] EU FP7 DIPLECS Deliverable D7. 2 (In situe strategy induction system) Beneficiary, D Windridge
[6] EU FP7 DIPLECS Deliverable D7. 1 (Prototype system for bootstrapping formalised strategies and associated logical representations) Beneficiary, D Windridge
[5] Article relating to the DIPLECS project arising from an interview I gave to The Engineer magazine: http://www.theengineer.co.uk/away-from-engineering/
[4] Coverage in the Daily Mail of my 3D Stereoscopic Laparoscopy Investigations:
http://www.dailymail.co.uk/health/article-1344688/3D-keyhole-surgery-performed-British-doctors.html
[3] Coverage in The Engineer magazine of 3D Stereoscopic Laperoscopy Investigations:
http://www.theengineer.co.uk/uk-hospital-performs-keyhole-surgery-using-3d-imagery/
[2] D. Windridge,
A Fluctuation Analysis for Optical Cluster Galaxies,
Ph.D. Thesis, University of Bristol, 1999
[1] Windridge, D, MERLIN observation of the gravitational lens system MG0414+0534, 1996, Research Report,
University of Manchester (Nuffield Radio Astronomy Laboratories, Jodrell Bank)
Spiteri, Michaela and Guillemaut, Jean-Yves and Windridge, David and Avula, Shivaram and Kumar, Ram and Lewis, Emma (2020) Fully-automated identification of imaging biomarkers for post-operative cerebellar mutism syndrome using longitudinal paediatric MRI. Neuroinformatics , 18 . pp. 151-162. ISSN 1539-2791
Windridge, David and Svensson, Henrik and Thill, Serge (2020) On the utility of dreaming: a general model for how learning in artificial agents can benefit from data hallucination. Adaptive Behavior . ISSN 1059-7123 (Published online first)
Windridge, David and Kammueller, Florian (2020) Edit distance Kernelization of NP theorem proving for polynomial-time machine learning of proof heuristics. In: FICC 2019: Future of Information and Communications Conference, 14-15 Mar 2019, San Francisco, USA.
Zia, Tehseen and Zahid, Usman and Windridge, David (2019) A generative adversarial strategy for modeling relation paths in knowledge base representation learning. In: KR2ML - Knowledge Representation and Reasoning Meets Machine Learning Workshop, NeurIPS 2019, Thirty-third Conference on Neural Information Processing Systems, 09-14 Dec 2019, Vancouver, Canada.
Ali, S. M. Murad and Augusto, Juan Carlos and Windridge, David (2019) Improving the adaptation process for a new smart home user. In: 39th SGAI International Conference on Artificial Intelligence (AI-2019)., 17-19 Dec 2019, Cambridge, UK..