Kittler, J.; Christmas, W.J.; Kostin, A.; Yan, F.; Kolonias, I.; Windridge, D.

A memory architecture and contextual reasoning framework for cognitive vision

Conference paper

Kittler, J., Christmas, W.J., Kostin, A., Yan, F., Kolonias, I. and Windridge, D. 2005. A memory architecture and contextual reasoning framework for cognitive vision. 14th Scandinavian Conference on Image Analysis. Joensuu, Finland 19 - 22 Jun 2005 Springer. https://doi.org/10.1007/11499145_36

ISBN
Type	Conference paper
Title	A memory architecture and contextual reasoning framework for cognitive vision
Authors	Kittler, J., Christmas, W.J., Kostin, A., Yan, F., Kolonias, I. and Windridge, D.
Abstract	One of the key requirements for a cognitive vision system to support reasoning is the possession of an effective mechanism to exploit context both for scene interpretation and for action planning. Context can be used effectively provided the system is endowed with a conducive memory architecture that supports contextual reasoning at all levels of processing, as well as a contextual reasoning framework. In this paper we describe a unified apparatus for reasoning using context, cast in a Bayesian reasoning framework. We also describe a modular memory architecture developed as part of the VAMPIRE* vision system which allows the system to store raw video data at the lowest level and its semantic annotation of monotonically increasing abstraction at the higher levels. By way of illustration, we use as an application for the memory system the automatic annotation of a tennis match.
Conference	14th Scandinavian Conference on Image Analysis
Proceedings Title	Image Analysis: 14th Scandinavian Conference, SCIA 2005, Joensuu, Finland, June 19-22, 2005, Proceedings
Series	Lecture Notes in Computer Science
Paperback	9783540263203
Electronic	9783540315667
Publisher	Springer
Publication dates
Print	2005
Publication process dates
Deposited	16 Sep 2025
Output status	Published
Digital Object Identifier (DOI)	https://doi.org/10.1007/11499145_36
Scopus EID	2-s2.0-26444612141

Permalink -

https://repository.mdx.ac.uk/item/2v33xy

Log in to edit

341
total views
0
total downloads
4
views this month
0
downloads this month

Export as

Related outputs

EEL-GA: an evolutionary clustering framework for energy-efficient 3D wireless sensor networks in smart forestry

Batool, F., Ali, K., Lasebae, A., Windridge, D. and Kiyani, A. 2025. EEL-GA: an evolutionary clustering framework for energy-efficient 3D wireless sensor networks in smart forestry. Sensors. 25 (17). https://doi.org/10.3390/s25175250

Judges on trial: the future of research on judicial decision-making

Dhami, M., Kajdanowicz, T., Windridge, D. and Boukacem-Zeghmouri, C. 2025. Judges on trial: the future of research on judicial decision-making. in: Shortland, N. and Alison, L. (ed.) Big Ideas in Forensic Psychology: Visions of a Forensic Future From Leading Voices in the Field Wiley.

Identifying social vulnerability profiles for coastal flood using supervised and unsupervised machine learning: a case study of Lekki peninsula, Lagos, Nigeria

Akindejoye, A., Viavattene, C., Priest, S. and Windridge, D. 2025. Identifying social vulnerability profiles for coastal flood using supervised and unsupervised machine learning: a case study of Lekki peninsula, Lagos, Nigeria. International Journal of Disaster Risk Reduction. 127. https://doi.org/10.1016/j.ijdrr.2025.105693

Classical to quantum knowledge distillation: a study on the impact of hybridization

Piperno, S., Vittori, G., Windridge, D., Rosato, A. and Panella, M. 2025. Classical to quantum knowledge distillation: a study on the impact of hybridization. International Joint Conference on Neural Networks (IJCNN) 2025. Rome, Italy 30 Jun - 05 Jul 2025 IEEE.

A latent diffusion approach to visual attribution in medical imaging

Siddiqui, A.A., Tirunagari, S., Zia, T. and Windridge, D. 2025. A latent diffusion approach to visual attribution in medical imaging. Scientific Reports. 15 (1). https://doi.org/10.1038/s41598-024-81646-x

Accelerating material discovery for CdTe solar cells using knowledge intense word embeddings

Liu, X., Barth, K., Windridge, D. and Xu, K. 2024. Accelerating material discovery for CdTe solar cells using knowledge intense word embeddings. 52nd Photovoltaic Specialist Conference. Seattle, WA, USA 09 - 14 Jun 2024 IEEE. pp. 0281-0283 https://doi.org/10.1109/pvsc57443.2024.10749288

Quantum enhanced knowledge distillation

Simone, P., Lavagna, L., De Falco, F,, Ceschini, A., Rosato, A., Windridge, D. and Panella, M. 2024. Quantum enhanced knowledge distillation. Quantum Techniques in Machine Learning 2024 Conference. Melbourne, Australia 24 - 29 Nov 2024

An evolutionary approach to automated class-specific data augmentation for image classification

Marc, S., Belavkin, R., Windridge, D. and Gao, X. 2024. An evolutionary approach to automated class-specific data augmentation for image classification. Moosaei, H., Hladík, M. and Pardalos, P. (ed.) 6th International Conference on the Dynamics of Information Systems. Prague, Czech Republic 03 - 06 Dec 2023 Springer. pp. 170–185 https://doi.org/10.1007/978-3-031-50320-7_12

Faithful Counterfactual Visual Explanations (FCVE)

Khan, B., Tariq, S., Zia, T., Ahsan, M. and Windridge, D. 2024. Faithful Counterfactual Visual Explanations (FCVE). Knowledge-Based Systems. 294. https://doi.org/10.1016/j.knosys.2024.111668

Resource saving via ensemble techniques for quantum neural networks

Incudini, M., Grossi, M., Ceschini, A., Mandarino, A., Panella, M., Vallecorsa, S. and Windridge, D. 2023. Resource saving via ensemble techniques for quantum neural networks. Quantum Machine Intelligence. 5 (2). https://doi.org/10.1007/s42484-023-00126-z

A topological features based quantum kernel

Incudini, M., Martini, F., Di Pierro, A. and Windridge, D. 2023. A topological features based quantum kernel. 7th International Conference on Quantum Techniques in Machine Learning. CERN, Geneva 19 - 24 Nov 2023

Interpretable chronic kidney disease risk prediction from clinical data using machine learning

Chennareddy, V., Tirunagari, S., Mohan, S., Windridge, D. and Balla, Y. 2023. Interpretable chronic kidney disease risk prediction from clinical data using machine learning. 16th Multi-Disciplinary International Conference on Artificial Intelligence (MIWAI 2023). Hyderabad, India 21 2023 - 22 Jul 2024 Springer. https://doi.org/10.1007/978-3-031-36402-0_63

Addressing challenges in healthcare big data analytics

Tirunagari, S., Mohan, S., Windridge, D. and Balla, Y. 2023. Addressing challenges in healthcare big data analytics. 16th Multi-Disciplinary International Conference on Artificial Intelligence (MIWAI 2023). Hyderabad, India 21 2023 - 22 Jul 2024 Springer. https://doi.org/10.1007/978-3-031-36402-0_70

Visual attribution using Adversarial Latent Transformations

Zia, T., Wahab, A., Windridge, D., Tirunagari, S. and Bhatti, N. 2023. Visual attribution using Adversarial Latent Transformations. Computers in Biology and Medicine. 166. https://doi.org/10.1016/j.compbiomed.2023.107521

Deep combination of radar with optical data for gesture recognition: role of attention in fusion architectures

Towakel, P., Windridge, D. and Nguyen, H. 2023. Deep combination of radar with optical data for gesture recognition: role of attention in fusion architectures. IEEE Transactions on Instrumentation and Measurement. 72, pp. 1-15. https://doi.org/10.1109/TIM.2023.3307768

The quantum path kernel: a generalized neural tangent kernel for deep quantum machine learning

Incudini, M., Grossi, M., Mandarino, A., Vallecorsa, S., Di Pierro, A. and Windridge, D. 2023. The quantum path kernel: a generalized neural tangent kernel for deep quantum machine learning. IEEE Transactions on Quantum Engineering. 4. https://doi.org/10.1109/TQE.2023.3287736

Pediatrics in artificial intelligence era: A systematic review on challenges, opportunities, and explainability

Balla, Y., Tirunagari, S. and Windridge, D. 2023. Pediatrics in artificial intelligence era: A systematic review on challenges, opportunities, and explainability. Indian Pediatrics. 60 (7), pp. 561-569. https://doi.org/10.1007/s13312-023-2936-8

Resource saving via ensemble techniques for quantum neural networks

Incudini, M., Grossi, M., Ceschini, A., Mandarino, A., Panella, M., Vallecorsa, S. and Windridge, D. 2023. Resource saving via ensemble techniques for quantum neural networks. https://doi.org/10.48550/arXiv.2303.11283

Reducing the dependency of having prior domain knowledge for effective online information retrieval

Zammit, O., Smith, S., Windridge, D. and De Raffaele, C. 2023. Reducing the dependency of having prior domain knowledge for effective online information retrieval. Expert Systems. 40 (4). https://doi.org/10.1111/exsy.13014

A user-guided personalization methodology to facilitate new smart home occupancy

Ali, S.M.M., Augusto, J., Windridge, D. and Ward, E. 2023. A user-guided personalization methodology to facilitate new smart home occupancy. Universal Access in the Information Society. 22 (3), pp. 869-891. https://doi.org/10.1007/s10209-022-00883-x

The quantum path kernel: A generalized quantum neural tangent kernel for deep quantum machine learning

Incudini, M., Grossi, M., Mandarino, A., Vallecorsa, S., Di Pierro, A. and Windridge, D. 2022. The quantum path kernel: A generalized quantum neural tangent kernel for deep quantum machine learning. https://doi.org/10.48550/arXiv.2212.11826

Discriminator-based adversarial networks for knowledge graph completion

Tubaishat, A., Zia, T., Faiz, R., Al Obediat, F., Shah, B. and Windridge, D. 2022. Discriminator-based adversarial networks for knowledge graph completion. Neural Computing and Applications. https://doi.org/10.1007/s00521-022-07680-w

A novel kernel based approach to arbitrary length symbolic data with application to type 2 diabetes risk

Nwegbu, N., Tirunagari, S. and Windridge, D. 2022. A novel kernel based approach to arbitrary length symbolic data with application to type 2 diabetes risk. Scientific Reports. 12 (1), pp. 1-16. https://doi.org/10.1038/s41598-022-08757-1

VANT-GAN: adversarial learning for discrepancy-based visual attribution in medical imaging

Zia, T., Murtaza, S., Bhatti, N., Windridge, D. and Nisar, Z. 2022. VANT-GAN: adversarial learning for discrepancy-based visual attribution in medical imaging. Pattern Recognition Letters. 156, pp. 112-118. https://doi.org/10.1016/j.patrec.2022.02.005

A generative adversarial network for single and multi-hop distributional knowledge base completion

Zia, T. and Windridge, D. 2021. A generative adversarial network for single and multi-hop distributional knowledge base completion. Neurocomputing. 461, pp. 543-551. https://doi.org/10.1016/j.neucom.2021.04.128

Generative Adversarial Networks (GANs) in networking: A comprehensive survey & evaluation

Navidan, H., Moshiri, P., Nabati, M., Shahbazian, R., Ghorashi, S., Shah-Mansouri, V. and Windridge, D. 2021. Generative Adversarial Networks (GANs) in networking: A comprehensive survey & evaluation. Computer Networks. 194, pp. 1-21. https://doi.org/10.1016/j.comnet.2021.108149

Multi-view convolutional recurrent neural networks for lung cancer nodule identification

Naeem Abid, M., Zia, T., Ghafoor, M. and Windridge, D. 2021. Multi-view convolutional recurrent neural networks for lung cancer nodule identification. Neurocomputing. 453, pp. 299-311. https://doi.org/10.1016/j.neucom.2020.06.144

A genetic deep learning model for electrophysiological soft robotics

Pandey, H. and Windridge, D. 2021. A genetic deep learning model for electrophysiological soft robotics. Balas, V., Jain, L., Balas, M. and Shahbazova, S. (ed.) 8th International Workshop on Soft Computing Applications. Arad, Romania 13 - 15 Sep 2018 Cham Springer. https://doi.org/10.1007/978-3-030-51992-6_12

Exposing students to new terminologies while collecting browsing search data (best technical paper)

Zammit, O., Smith, S., Windridge, D. and De Raffaele, C. 2020. Exposing students to new terminologies while collecting browsing search data (best technical paper). 40th SGAI International Conference on Artificial Intelligence, AI 2020. Cambridge, UK 15 - 17 Dec 2020 Cham Springer. https://doi.org/10.1007/978-3-030-63799-6_1

On the utility of dreaming: a general model for how learning in artificial agents can benefit from data hallucination

Windridge, D., Svensson, H. and Thill, S. 2021. On the utility of dreaming: a general model for how learning in artificial agents can benefit from data hallucination. Adaptive Behavior. 29 (3), pp. 267-280. https://doi.org/10.1177/1059712319896489

Epileptic seizure detection using constrained singular spectrum analysis and 1D-local binary patterns

Ramanna, S., Tirunagari, S. and Windridge, D. 2020. Epileptic seizure detection using constrained singular spectrum analysis and 1D-local binary patterns. Health and Technology. 10 (3), pp. 699-709. https://doi.org/10.1007/s12553-019-00395-4

Editorial to special issue on hybrid artificial intelligence and machine learning technologies in intelligent systems

Pandey, H., Bessis, N., Das, S., Windridge, D. and Chaudhary, A. 2020. Editorial to special issue on hybrid artificial intelligence and machine learning technologies in intelligent systems. Neural Computing and Applications. 32 (12), pp. 7743-7745. https://doi.org/10.1007/s00521-020-04903-w

A low-complexity trajectory privacy preservation approach for indoor fingerprinting positioning systems

Sazdar, A.M., Ghorashi, S.A., Moghtadaiee, V., Khonsari, A. and Windridge, D. 2020. A low-complexity trajectory privacy preservation approach for indoor fingerprinting positioning systems. Journal of Information Security and Applications. 53. https://doi.org/10.1016/j.jisa.2020.102515

Revisiting direct neuralisation of first-order logic

Gunn, I. and Windridge, D. 2018. Revisiting direct neuralisation of first-order logic. NeSy 2018 : Thirteenth International Workshop on Neural-Symbolic Learning and Reasoning. Prague, Czech Republic 23 - 24 Aug 2018

A generative adversarial strategy for modeling relation paths in knowledge base representation learning

Zia, T., Zahid, U. and Windridge, D. 2019. A generative adversarial strategy for modeling relation paths in knowledge base representation learning. KR2ML - Knowledge Representation and Reasoning Meets Machine Learning Workshop, NeurIPS 2019, Thirty-third Conference on Neural Information Processing Systems. Vancouver, Canada 09 - 14 Dec 2019

Fully-automated identification of imaging biomarkers for post-operative cerebellar mutism syndrome using longitudinal paediatric MRI

Spiteri, M., Guillemaut, J., Windridge, D., Avula, S., Kumar, R. and Lewis, E. 2020. Fully-automated identification of imaging biomarkers for post-operative cerebellar mutism syndrome using longitudinal paediatric MRI. Neuroinformatics. 18 (1), pp. 151-162. https://doi.org/10.1007/s12021-019-09427-w

Automatic delineation of kidney region in DCE-MRI

Tirunagari, S., Poh, N., Wells, K., Bober, M., Gorden, I. and Windridge, D. 2019. Automatic delineation of kidney region in DCE-MRI.

A family of globally optimal branch-and-bound algorithms for 2D–3D correspondence-free registration

Brown, M., Windridge, D. and Guillemaut, J. 2019. A family of globally optimal branch-and-bound algorithms for 2D–3D correspondence-free registration. Pattern Recognition. 93, pp. 36-54. https://doi.org/10.1016/j.patcog.2019.04.002

An approach to human-machine teaming in legal investigations using anchored narrative visualisation and machine learning

Attfield, S., Fields, B., Windridge, D. and Xu, K. 2019. An approach to human-machine teaming in legal investigations using anchored narrative visualisation and machine learning. Conrad, J., Pickens, J., Jones, A., Baron, J. and Henseler, H. (ed.) First International Workshop on AI and Intelligent Assistance for Legal Professionals in the Digital Workplace (LegalAIIA 2019).. Montreal, Canada 17 Jun 2019 CEUR Workshop Proceedings. pp. 7-11

Improving the adaptation process for a new smart home user

Ali, S., Augusto, J. and Windridge, D. 2019. Improving the adaptation process for a new smart home user. Bramer, M. and Petridis, M. (ed.) AI-2019 Thirty-ninth SGAI International Conference on Artificial Intelligence. Cambridge, United Kingdom 17 - 19 Dec 2019 Springer. https://doi.org/10.1007/978-3-030-34885-4_32

A survey of user-centred approaches for smart home transfer learning and new user home automation adaptation

Ali, M., Augusto, J. and Windridge, D. 2019. A survey of user-centred approaches for smart home transfer learning and new user home automation adaptation. Applied Artificial Intelligence. 33 (8), pp. 747-774. https://doi.org/10.1080/08839514.2019.1603784

A comprehensive classification of deep learning libraries

Pandey, H. and Windridge, D. 2019. A comprehensive classification of deep learning libraries. Yang, X.S., Sherratt, S., Dey, N. and Joshi, A. (ed.) 3rd International Congress on Information and Communication Technology. London, UK 27 - 28 Feb 2018 Singapore Springer. pp. 427-435 https://doi.org/10.1007/978-981-13-1165-9_40

Edit distance Kernelization of NP theorem proving for polynomial-time machine learning of proof heuristics

Windridge, D. and Kammueller, F. 2020. Edit distance Kernelization of NP theorem proving for polynomial-time machine learning of proof heuristics. FICC 2019: Future of Information and Communications Conference. San Francisco, USA 14 - 15 Mar 2019 Springer. pp. 271-283 https://doi.org/10.1007/978-3-030-12385-7_22

Criminal pattern identification based on modified K-means clustering

Aljrees, T., Shi, D., Windridge, D. and Wong, B. 2016. Criminal pattern identification based on modified K-means clustering. 2016 International Conference on Machine Learning and Cybernetics (ICMLC). 2, pp. 799-806. https://doi.org/10.1109/ICMLC.2016.7872990

On the intrinsic limits to representationally-adaptive machine-learning

Windridge, D. 2015. On the intrinsic limits to representationally-adaptive machine-learning. ArXiv e-prints.

Data governance in the health industry: investigating data quality dimensions within a big data context

Juddoo, S., George, C., Duquenoy, P. and Windridge, D. 2018. Data governance in the health industry: investigating data quality dimensions within a big data context. Applied System Innovation. 1 (4), pp. 1-16. https://doi.org/10.3390/asi1040043

Quantum error-correcting output codes

Windridge, D., Mengoni, R. and Nagarajan, R. 2018. Quantum error-correcting output codes. International Journal of Quantum Information. 16 (8). https://doi.org/10.1142/S0219749918400038

Representational fluidity in embodied (artificial) cognition

Windridge, D. and Thill, S. 2018. Representational fluidity in embodied (artificial) cognition. Biosystems. 172, pp. 9-17. https://doi.org/10.1016/j.biosystems.2018.07.007

An improved block matching algorithm for motion estimation in video sequences and application in robotics

Bhattacharjee, K., Kumar, S., Pandey, H., Pant, M., Windridge, D. and Chaudhary, A. 2018. An improved block matching algorithm for motion estimation in video sequences and application in robotics. Computers & Electrical Engineering. 68, pp. 92-106. https://doi.org/10.1016/j.compeleceng.2018.03.045

Proteomic identification and characterization of hepatic glyoxalase 1 dysregulation in non-alcoholic fatty liver disease

Spanos, C., Maldonado, E.M., Fisher, C.P., Leenutaphong, P., Oviedo-Orta, E., Windridge, D., Salguero, F.J., Bermúdez-Fajardo, A., Weeks, M.E., Evans, C., Corfe, B.M., Rabbani, N., Thornalley, P.J., Miller, M.H., Wang, H., Dillon, J.F., Quaglia, A., Dhawan, A., Fitzpatrick, E. and Moore, J.B. 2018. Proteomic identification and characterization of hepatic glyoxalase 1 dysregulation in non-alcoholic fatty liver disease. Proteome Science. 16 (1). https://doi.org/10.1186/s12953-018-0131-y

Addressing VAST 2016 mini challenge 2 with POLAR kermode, classifier, excel on a power wall and data timelines

Attfield, S., Hewitt, D., Xu, K., Passmore, P., Wagstaff, A., Phillips, G., Windridge, D., Dash, G., Chapman, R. and Mason, L. 2016. Addressing VAST 2016 mini challenge 2 with POLAR kermode, classifier, excel on a power wall and data timelines. IEEE VAST Challenge 2016. Baltimore, MD, USA 23 Oct 2016

Quantum Bootstrap Aggregation

Windridge, D. and Nagarajan, R. 2017. Quantum Bootstrap Aggregation. de Barros, J., Coecke, B. and Pothos, E. (ed.) Quantum Interaction. San Francisco, CA, USA 20 - 22 Jul 2016 Springer. pp. 115-121 https://doi.org/10.1007/978-3-319-52289-0_9

A Hybrid Multi-Layer Architecture for Autonomous Vehicles Utilising a Hierarchical Perception-Action Dream Simulation Mechanism

Windridge, D., Gunn, I.A.D., Da Lio, M., Mazzalai, A., Thill, S., Svensson, H., Anderson, S., Blenkinsop, A., Gurney, K., James, S., Math, R., Berghoefer, E., Yueksel, M., Saroldi, A., Andreone, L. and Heich, H.-J. 2017. A Hybrid Multi-Layer Architecture for Autonomous Vehicles Utilising a Hierarchical Perception-Action Dream Simulation Mechanism. EUCognition 2017 Conference. Zürich, Switzerland 23 - 24 Nov 2017

Hamming distance kernelisation via topological quantum computation

Di Pierro, A., Mengoni, R., Nagarajan, R. and Windridge, D. 2017. Hamming distance kernelisation via topological quantum computation. Martín-Vide C., Neruda R. and Vega-Rodríguez M. (ed.) 6th International Conference on the Theory and Practice of Natural Computing. Prague, Czech Republic 18 - 20 Dec 2017 Springer. pp. 269-280 https://doi.org/10.1007/978-3-319-71069-3_21

Emergent intentionality in perception-action subsumption hierarchies

Windridge, D. 2017. Emergent intentionality in perception-action subsumption hierarchies. Frontiers in Robotics and AI. 4. https://doi.org/10.3389/frobt.2017.00038

Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition

Tirunagari, S., Poh, N., Wells, K., Bober, M., Gorden, I. and Windridge, D. 2017. Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition. Machine Vision and Applications. 28 (3-4), pp. 393-407. https://doi.org/10.1007/s00138-017-0835-5

A generalised framework for saliency-based point feature detection

Brown, M., Windridge, D. and Guillemaut, J. 2017. A generalised framework for saliency-based point feature detection. Computer Vision and Image Understanding. 157, pp. 117-137. https://doi.org/10.1016/j.cviu.2016.09.008

Post-operative pediatric cerebellar mutism syndrome and its association with hypertrophic olivary degeneration

Avula, S., Spiteri, M., Kumar, R., Lewis, E., Harave, S., Windridge, D., Ong, C. and Pizer, B. 2016. Post-operative pediatric cerebellar mutism syndrome and its association with hypertrophic olivary degeneration. Quantitative Imaging in Medicine and Surgery. 6 (5), pp. 535-544. https://doi.org/10.21037/qims.2016.10.11

Criminal pattern identification based on modified K-means clustering

Aljrees, T., Shi, D., Windridge, D. and Wong, B. 2016. Criminal pattern identification based on modified K-means clustering. 2016 International Conference on Machine Learning and Cybernetics. Jeju, South Korea 10 - 13 Jul 2016 IEEE. pp. 799-806 https://doi.org/10.1109/ICMLC.2016.7872990

Can DMD obtain a scene background in color?

Tirunagari, S., Poh, N., Bober, M. and Windridge, D. 2016. Can DMD obtain a scene background in color? 2016 International Conference on Image, Vision and Computing (ICIVC). Portsmouth, UK 03 - 05 Aug 2016 pp. 46-50 https://doi.org/10.1109/ICIVC.2016.7571272

Classification of fibroglandular tissue distribution in the breast based on radiotherapy planning CT

Juneja, P., Evans, P., Windridge, D. and Harris, E. 2016. Classification of fibroglandular tissue distribution in the breast based on radiotherapy planning CT. BMC Medical Imaging. 16 (1). https://doi.org/10.1186/s12880-016-0107-2

Kernel combination via debiased object correspondence analysis

Windridge, D. and Yan, F. 2016. Kernel combination via debiased object correspondence analysis. Information Fusion. 27, pp. 228-239. https://doi.org/10.1016/j.inffus.2015.02.002

Identifying quantitative imaging features of posterior fossa syndrome in longitudinal MRI

Spiteri, M., Windridge, D., Avula, S., Kumar, R. and Lewis, E. 2015. Identifying quantitative imaging features of posterior fossa syndrome in longitudinal MRI. Journal of Medical Imaging. 2 (4), p. 044502. https://doi.org/10.1117/1.JMI.2.4.044502

Identifying similar patients using self-organising maps: a case study on type-1 diabetes self-care survey responses

Tirunagari, S., Poh, N., Hu, G. and Windridge, D. 2015. Identifying similar patients using self-organising maps: a case study on type-1 diabetes self-care survey responses. https://doi.org/10.48550/arXiv.1503.06316

Longitudinal MRI assessment: the identification of relevant features in the development of posterior fossa syndrome in children

Spiteri, M., Lewis, E., Windridge, D. and Avula, S. 2015. Longitudinal MRI assessment: the identification of relevant features in the development of posterior fossa syndrome in children. Medical imaging 2015: Computer-Aided Diagnosis. Orlando, Florida, United States 21 Feb 2015 Society of Photo-Optical Instrumentation Engineers. https://doi.org/10.1117/12.2081591

Windowed DMD as a microtexture descriptor for finger vein counter-spoofing in biometrics

Tirunagari, S., Poh, N., Bober, M. and Windridge, D. 2015. Windowed DMD as a microtexture descriptor for finger vein counter-spoofing in biometrics. 2015 IEEE International Workshop on Information Forensics and Security (WIFS). Rome, Italy 16 - 19 Nov 2015 Institute of Electrical and Electronics Engineers (IEEE). pp. 1-6 https://doi.org/10.1109/WIFS.2015.7368599

Globally optimal 2D-3D registration from points or lines without correspondences

Brown, M., Windridge, D. and Guillemaut, J. 2015. Globally optimal 2D-3D registration from points or lines without correspondences. 2015 IEEE International Conference on Computer Vision (ICCV). Santiago, Chile 07 - 13 Dec 2015 Institute of Electrical and Electronics Engineers (IEEE). pp. 2111-2119 https://doi.org/10.1109/ICCV.2015.244

A generalisable framework for saliency-based line segment detection

Brown, M., Windridge, D. and Guillemaut, J. 2015. A generalisable framework for saliency-based line segment detection. Pattern Recognition. 48 (12), pp. 3993-4011. https://doi.org/10.1016/j.patcog.2015.06.015

A novel Markov logic rule induction strategy for characterizing sports video footage

Windridge, D., Kittler, J., De Campos, T., Yan, F., Christmas, W. and Khan, A. 2015. A novel Markov logic rule induction strategy for characterizing sports video footage. IEEE MultiMedia. 22 (2), pp. 24-35. https://doi.org/10.1109/MMUL.2014.36

Artificial co-drivers as a universal enabling technology for future intelligent vehicles and transportation systems

Da Lio, M., Biral, F., Bertolazzi, E., Galvani, M., Bosetti, P., Windridge, D., Saroldi, A. and Tango, F. 2015. Artificial co-drivers as a universal enabling technology for future intelligent vehicles and transportation systems. IEEE Transactions on Intelligent Transportation Systems. 16 (1), pp. 244-263. https://doi.org/10.1109/TITS.2014.2330199

Breast cancer data analytics with missing values: a study on ethnic, age and income groups

Tirunagari, S., Poh, N., Abdulrahman, H., Nemmour, N. and Windridge, D. 2015. Breast cancer data analytics with missing values: a study on ethnic, age and income groups. ArXiv e-prints: Quantitative Biology > Quantitative Methods. https://doi.org/10.48550/arXiv.1503.03680

Detection of face spoofing using visual dynamics

Tirunagari, S., Poh, N., Windridge, D., Iorliam, A., Suki, N. and Ho, A. 2015. Detection of face spoofing using visual dynamics. IEEE Transactions on Information Forensics and Security. 10 (4), pp. 762-777. https://doi.org/10.1109/TIFS.2015.2406533

Multilevel Chinese takeaway process and label-based processes for rule induction in the context of automated sports video annotation

Khan, A., Windridge, D. and Kittler, J. 2014. Multilevel Chinese takeaway process and label-based processes for rule induction in the context of automated sports video annotation. IEEE Transactions on Cybernetics. 44 (10), pp. 1910-1923. https://doi.org/10.1109/TCYB.2014.2299955

Domain anomaly detection in machine perception: a system architecture and taxonomy

Kittler, J., Christmas, W., De Campos, T., Windridge, D., Yan, F., Illingworth, J. and Osman, M. 2014. Domain anomaly detection in machine perception: a system architecture and taxonomy. IEEE Transactions on Pattern Analysis and Machine Intelligence. 36 (5), pp. 845-859. https://doi.org/10.1109/TPAMI.2013.209

A saliency-based framework for 2D-3D registration

Brown, M., Guillemaut, J. and Windridge, D. 2014. A saliency-based framework for 2D-3D registration. 9th International Conference on Computer Vision Theory and Applications (VISAPP 2014). Lisbon, Portugal 05 - 08 Jan 2014 SCITEPRESS - Science and Technology Publications. pp. 265-273 https://doi.org/10.5220/0004675402650273

Supervised selective kernel fusion for membrane protein prediction

Tatarchuk, A., Sulimova, V., Torshin, I., Mottl, V. and Windridge, D. 2014. Supervised selective kernel fusion for membrane protein prediction. Comin, M., Käll, L., Marchiori, E., Ngom, A. and Rajapakse, J. (ed.) 9th IAPR International Conference Pattern Recognition in Bioinformatics (PRIB 2014). Stockholm, Sweden 21 - 23 Aug 2014 Springer. pp. 98-109 https://doi.org/10.1007/978-3-319-09192-1_9

Challenges in designing an online healthcare platform for personalised patient analytics

Poh, N., Tirunagari, S. and Windridge, D. 2014. Challenges in designing an online healthcare platform for personalised patient analytics. 2014 IEEE Symposium on Computational Intelligence in Big Data (CIBD). Orlando, FL., USA 09 - 12 Dec 2014 IEEE. pp. 1-6 https://doi.org/10.1109/CIBD.2014.7011526

Patient level analytics using self-organising maps: a case study on type-1 diabetes self-care survey responses

Tirunagari, S., Poh, N., Aliabadi, K., Windridge, D. and Cooke, D. 2014. Patient level analytics using self-organising maps: a case study on type-1 diabetes self-care survey responses. 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). Orlando, FL., USA 09 - 12 Dec 2014 Institute of Electrical and Electronics Engineers (IEEE). pp. 304-309 https://doi.org/10.1109/CIDM.2014.7008682

Non-enumerative cross validation for the determination of structural parameters in feature-selective SVMs

Chernousova, E., Levdik, P., Tatarchuk, A., Mottl, V. and Windridge, D. 2014. Non-enumerative cross validation for the determination of structural parameters in feature-selective SVMs. 22nd International Conference on Pattern Recognition ICPR 2014. Stockholm, Sweden 24 - 28 Aug 2014 Institute of Electrical and Electronics Engineers (IEEE). pp. 3654-3659 https://doi.org/10.1109/ICPR.2014.628

Linear regression via elastic net: non-enumerative leave-one-out verification of feature selection

Chernousova, E., Razin, N., Krasotkina, O., Mottl, V. and Windridge, D. 2014. Linear regression via elastic net: non-enumerative leave-one-out verification of feature selection. in: Aleskerov, F., Goldengorin, B. and Pardalos, P. (ed.) Clusters, Orders, and Trees: Methods and Applications: In Honor of Boris Mirkin's 70th Birthday New York Springer.

Automatic annotation of tennis games: an integration of audio, vision, and learning

Yan, F., Kittler, J., Windridge, D., Christmas, W., Mikolajczyk, K., Cox, S. and Huang, Q. 2014. Automatic annotation of tennis games: an integration of audio, vision, and learning. Image and Vision Computing. 32 (11), pp. 896-903. https://doi.org/10.1016/j.imavis.2014.08.004

A kernel-based framework for medical big-data analytics

Windridge, D. and Bober, M. 2014. A kernel-based framework for medical big-data analytics. in: Interactive Knowledge Discovery and Data Mining in Biomedical Informatics: State-of-the-Art and Future Challenges Springer. pp. 197-208

Trained eyes: experience promotes adaptive gaze control in dynamic and uncertain visual environments

Taya, S., Windridge, D. and Osman, M. 2013. Trained eyes: experience promotes adaptive gaze control in dynamic and uncertain visual environments. PLoS ONE. 8 (8). https://doi.org/10.1371/journal.pone.0071371

High throughput screening for mammography using a human-computer interface with rapid serial visual presentation (RSVP)

Abbey, C., Hope, C., Sterr, A., Elangovan, P., Geades, N., Windridge, D., Young, K., Wells, K. and Mello-Thoms, C. 2013. High throughput screening for mammography using a human-computer interface with rapid serial visual presentation (RSVP). SPIE Proceedings Vol. 8673. https://doi.org/10.1117/12.2007557

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. and Osman, M. 2012. Looking to score: the dissociation of goal influence on eye movement and meta-attentional allocation in a complex dynamic natural scene. PLoS ONE. 7 (6). https://doi.org/10.1371/journal.pone.0039060

Automatic annotation of court games with structured output learning

Yan, F., Kittler, J., Mikolajczyk, K. and Windridge, D. 2012. Automatic annotation of court games with structured output learning. 21st International Conference on Pattern Recognition. Tsukuba, Japan 11 - 15 Nov 2012 IEEE. pp. 3577-3580 https://doi.org/https://ieeexplore.ieee.org/document/6460938

Application of the multi-modal relevance vector machine to the problem of protein secondary structure prediction

Razin, N., Sungurov, D., Mottl, V., Torshin, I., Sulimova, V., Seredin, O. and Windridge, D. 2012. Application of the multi-modal relevance vector machine to the problem of protein secondary structure prediction. 7th IAPR International Conference on Pattern Recognition in Bioinformatics. Tokyo, Japan 08 - 10 Nov 2012 Springer. pp. 153-165 https://doi.org/10.1007/978-3-642-34123-6_14

Anomaly detection and knowledge transfer in automatic sports video annotation

Almajai, I., Yan, F., De Campos, T., Khan, A., Christmas, W., Windridge, D. and Kittler, J. 2011. Anomaly detection and knowledge transfer in automatic sports video annotation. in: Weinshall, D., Anemüller, J. and Gool, L. (ed.) Detection and Identification of Rare Audio-visual Cues Springer. pp. 109-117

An evaluation of bags-of-words and spatio-temporal shapes for action recognition

de Campos, T., Barnard, M., Mikolajczyk, K., Kittler, J., Yan, F., Christmas, W. and Windridge, D. 2011. An evaluation of bags-of-words and spatio-temporal shapes for action recognition. 2011 IEEE Workshop on Applications of Computer Vision (WACV). Kona, HI, USA 05 - 07 Jan 2011 IEEE. https://doi.org/10.1109/WACV.2011.5711524

A modified neutral point method for kernel-based fusion of pattern-recognition modalities with incomplete data sets

Panov, M., Tatarchuk, A., Mottl, V. and Windridge, D. 2011. A modified neutral point method for kernel-based fusion of pattern-recognition modalities with incomplete data sets. 10th International Workshop on Multiple Classifier Systems. Naples, Italy 15 - 17 Jun 2011 Springer. https://doi.org/10.1007/978-3-642-21557-5_15

Ball event recognition using HMM for automatic tennis annotation

Almajai, I., Kittler, J., De Campos, T., Christmas, W., Yan, F., Windridge, D. and Khan, A. 2010. Ball event recognition using HMM for automatic tennis annotation. 2010 IEEE International Conference on Image Processing. Hong Kong, China 26 - 29 Sep 2010 IEEE. https://doi.org/10.1109/ICIP.2010.5652415

Adaptive, perception-action-based cognitive modelling of human driving behaviour using control, gaze and signal inputs

Shaukat, A., Windridge, D., Hollnagel, E., Macchi, L. and Kittler, J. 2010. Adaptive, perception-action-based cognitive modelling of human driving behaviour using control, gaze and signal inputs. Brain Inspired Cognitive Systems - BICS 2010. Madrid, Spain 14 - 16 Jul 2010

A support kernel machine for supervised selective combining of diverse pattern-recognition modalities

Tatarchuk, A., Urlov, E., Mottl, V. and Windridge, D. 2010. A support kernel machine for supervised selective combining of diverse pattern-recognition modalities. 9th International Workshop on Multiple Classifier Systems. Cairo, Egypt 07 - 09 Apr 2010 Springer. https://doi.org/10.1007/978-3-642-12127-2_17

Addressing missing values in kernel-based multimodal biometric fusion using neutral point substitution

Poh, N., Windridge, D., Mottl, V., Tatarchuk, A. and Eliseyev, A. 2010. Addressing missing values in kernel-based multimodal biometric fusion using neutral point substitution. IEEE Transactions on Information Forensics and Security. 5 (3), pp. 461-469. https://doi.org/10.1109/TIFS.2010.2053535

A linear-complexity reparameterisation strategy for the hierarchical bootstrapping of capabilities within perception-action architectures

Shevchenko, M., Windridge, D. and Kittler, J. 2009. A linear-complexity reparameterisation strategy for the hierarchical bootstrapping of capabilities within perception-action architectures. Image and Vision Computing. 27 (11), pp. 1702-1714. https://doi.org/10.1016/j.imavis.2008.12.002

An entropy-based approach to the hierarchical acquisition of perception-action capabilities

Windridge, D., Shevchenko, M. and Kittler, J. 2008. An entropy-based approach to the hierarchical acquisition of perception-action capabilities. 4th International Workshop on Cognitive Vision. Santorini, Greece 12 May 2008 Springer. https://doi.org/10.1007/978-3-540-92781-5_7

A linguistic feature vector for the visual interpretation of sign language

Bowden, R., Windridge, D., Kadir, T., Zisserman, A. and Brady, M. 2004. A linguistic feature vector for the visual interpretation of sign language. 8th European Conference on Computer Vision. Prague, Czech Republic 11 - 14 May 2004 Springer. https://doi.org/10.1007/978-3-540-24670-1_30

A general strategy for hidden markov chain parameterisation in composite feature-spaces

Windridge, D., Bowden, R. and Kittler, J. 2004. A general strategy for hidden markov chain parameterisation in composite feature-spaces. Joint IAPR International Workshops, SSPR 2004 and SPR 2004. Lisbon, Portugal 18 - 20 Aug 2004 Springer. pp. 1069-1077 https://doi.org/10.1007/978-3-540-27868-9_118

A morphologically optimal strategy for classifier combination: Multiple expert fusion as a tomographic process

Windridge, D. and Kittler, J. 2003. A morphologically optimal strategy for classifier combination: Multiple expert fusion as a tomographic process. IEEE Transactions on Pattern Analysis and Machine Intelligence. 25 (3), pp. 343-353. https://doi.org/10.1109/TPAMI.2003.1182097