Jim Austin

Clement Creusot, Nick Pears, Jim Austin: A Machine-Learning Approach to Keypoint Detection and Landmarking on 3D Meshes. International Journal of Computer Vision 102(1-3): 146-179 (2013)

Clement Creusot, Nick Pears, Jim Austin: 3D landmark model discovery from a registered set of organic shapes. CVPR Workshops 2012: 57-64

James Austin, Stephen Hobson, Nathan Burles, Simon O'Keefe: A Rule Chaining Architecture Using a Correlation Matrix Memory. ICANN (1) 2012: 49-56

Victoria J. Hodge, Tom Jackson, Jim Austin: A Binary Neural Network Framework for Attribute Selection and Prediction. IJCCI 2012: 510-515

Paul Townend, Colin C. Venters, Lydia Lau, Karim Djemame, Vania Dimitrova, Alison Marshall, Jie Xu, Charlie Dibsdale, Nick Taylor, Jim Austin, John McAvoy, Martyn Fletcher, Stephen Hobson: A Framework for Improving Trust in Dynamic Service-Oriented Systems. ISORC Workshops 2012: 136-141

Sanil Shanker KP, Elizabeth Sherly, Jim Austin: A Note on Two Applications of Logical Matching Strategy. Applied Artificial Intelligence 25(8): 708-720 (2011)

Jim Austin, Tom Jackson, Martyn Fletcher, Mark Jessop, Bojian Liang, Mike Weeks, Leslie Smith, Colin Ingram, Paul Watson: CARMEN: Code analysis, Repository and Modeling for e-Neuroscience. Procedia CS 4: 768-777 (2011)

Clement Creusot, Nick Pears, Jim Austin: Automatic Keypoint Detection on 3D Faces Using a Dictionary of Local Shapes. 3DIMPVT 2011: 204-211

Colin C. Venters, Paul Townend, Lydia Lau, Karim Djemame, Vania Dimitrova, Alison Marshall, Jie Xu, Charlie Dibsdale, Nick Taylor, Jim Austin, John McAvoy, Martyn Fletcher, Stephen Hobson: Provenance: Current directions and future challenges for service oriented computing. SOSE 2011: 262-267

Victoria J. Hodge, Simon O'Keefe, Jim Austin: A binary neural shape matcher using Johnson Counters and chain codes. Neurocomputing 72(4-6): 693-703 (2009)

Stephen Hobson, Jim Austin: Improved Storage Capacity in Correlation Matrix Memories Storing Fixed Weight Codes. ICANN (1) 2009: 728-736

Quan Ju, Simon O'Keefe, Jim Austin: Binary neural network based 3D facial feature localization. IJCNN 2009: 1462-1469

Zezhi Chen, Nick Pears, Michael Freeman, Jim Austin: Background Subtraction in Video Using Recursive Mixture Models, Spatio-Temporal Filtering and Shadow Removal. ISVC (2) 2009: 1141-1150

Thomas Heseltine, Nick Pears, Jim Austin: Three-dimensional face recognition using combinations of surface feature map subspace components. Image Vision Comput. 26(3): 382-396 (2008)

Martyn Fletcher, Bojian Liang, Leslie Smith, Alastair Knowles, Tom Jackson, Mark Jessop, Jim Austin: Neural network based pattern matching and spike detection tools and services - in the CARMEN neuroinformatics project. Neural Networks 21(8): 1076-1084 (2008)

Zeshan Kurd, Tim Kelly, Jim Austin: Developing artificial neural networks for safety critical systems. Neural Computing and Applications 16(1): 11-19 (2007)

Victoria J. Hodge, John P. Eakins, James Austin: Inducing a perceptual relevance shape classifier. CIVR 2007: 138-145

Reinier H. van Leuken, M. Fatih Demirci, Victoria J. Hodge, Jim Austin, Remco C. Veltkamp: Layout indexing of trademark images. CIVR 2007: 525-532

Nimish Shah, Simon O'Keefe, Jim Austin: The Improved Correlation Matrix Memory (CMML). IJCNN 2007: 1168-1173

Victoria J. Hodge, Simon O'Keefe, Jim Austin: A binary neural decision table classifier. Neurocomputing 69(16-18): 1850-1859 (2006)

Martyn Fletcher, Tom Jackson, Mark Jessop, Bojian Liang, Jim Austin: The Signal Data Explorer: A High Performance Grid based Signal Search Tool for use in Distributed Diagnostic Applications. CCGRID 2006: 217-224

Victoria J. Hodge, Garry Hollier, John P. Eakins, Jim Austin: Eliciting Perceptual Ground Truth for Image Segmentation. CIVR 2006: 320-329

Jim Austin, Aaron Turner, Sujeewa Alwis: Grid Enabling Data De-Duplication. e-Science 2006: 2

Victoria J. Hodge, Jim Austin: A binary neural k-nearest neighbour technique. Knowl. Inf. Syst. 8(3): 276-291 (2005)

Michael Freeman, Jim Austin: Designing a Binary Neural Network Co-processor. DSD 2005: 223-227

Stefan Klinger, Jim Austin: Chemical similarity searching using a neural graph matcher. ESANN 2005: 479-484

Michael Freeman, Michael Weeks, Jim Austin: Hardware implementation of similarity functions. IADIS AC 2005: 329-332

Biswa Sengupta, Jim Austin, Gary Green: Modeling of Dual-Route Fear Conditioning Paradigm in the Auditory Cortex. IICAI 2005: 3632-3644

Victoria J. Hodge, Jim Austin: A Survey of Outlier Detection Methodologies. Artif. Intell. Rev. 22(2): 85-126 (2004)

Andy Pasley, Jim Austin: Distribution forecasting of high frequency time series. Decision Support Systems 37(4): 501-513 (2004)

Victoria J. Hodge, Ken Lees, Jim Austin: A high performance k-NN approach using binary neural networks. Neural Networks 17(3): 441-458 (2004)

Thomas Heseltine, Nick Pears, Jim Austin: Three-Dimensional Face Recognition Using Surface Space Combinations. BMVC 2004: 1-10

Jim Austin: A Grid Based Diagnostics and Prognosis System for Rolls Royce Aero Engines: The DAME Project. CLADE 2004: 2

Thomas Heseltine, Nick Pears, Jim Austin: Three-Dimensional Face Recognition: A Fishersurface Approach. ICIAR (2) 2004: 684-691

Thomas Heseltine, Nick Pears, Jim Austin: Three-dimensional face recognition: an eigensurface approach. ICIP 2004: 1421-1424

Zeshan Kurd, Tim P. Kelly, Jim Austin: Exploiting Safety Constraints in Fuzzy Self-organising Maps for Safety Critical Applications. IDEAL 2004: 266-271

Bojian Liang, Jim Austin: Mining Large Engineering Data Sets on the Grid Using AURA. IDEAL 2004: 430-436

Suresh Manandhar, Jim Austin, Uday B. Desai, Yoshio Oyanagi, Asoke K. Talukder (Eds.): Applied Computing, Second Asian Applied Computing Conference, AACC 2004, Kathmandu, Nepal, October 29-31, 2004. Proceedings. Lecture Notes in Computer Science 3285, Springer 2004, isbn 3-540-23659-7

Victoria J. Hodge, Jim Austin: A Comparison of Standard Spell Checking Algorithms and a Novel Binary Neural Approach. IEEE Trans. Knowl. Data Eng. 15(5): 1073-1081 (2003)

Thomas Heseltine, Nick Pears, Jim Austin, Zezhi Chen: Face Recognition: A Comparison of Appearance-Based Approaches. DICTA 2003: 59-68

Michael Weeks, Victoria J. Hodge, Simon O'Keefe, Jim Austin, Ken Lees: Improved AURA k-Nearest Neighbour Approach. IWANN (2) 2003: 663-670

Victoria J. Hodge, Jim Austin: Hierarchical word clustering - automatic thesaurus generation. Neurocomputing 48(1-4): 819-846 (2002)

Victoria J. Hodge, Jim Austin: A comparison of a novel neural spell checker and standard spell checking algorithms. Pattern Recognition 35(11): 2571-2580 (2002)

Garry Hollier, Jim Austin: Novelty detection for strain-gauge degradation using maximally correlated components. ESANN 2002: 257-262

Andy Pasley, Jim Austin: High frequency forecasting with associative memories. ESANN 2002: 433-438

Michael Weeks, Victoria J. Hodge, Jim Austin: Scalability of a Distributed Neural Information Retrieval System. HPDC 2002: 423

Michael Weeks, Victoria J. Hodge, Jim Austin: A Hardware-Accelerated Novel IR System. PDP 2002: 283-

Victoria J. Hodge, Jim Austin: An evaluation of standard retrieval algorithms and a binary neural approach. Neural Networks 14(3): 287-303 (2001)

Victoria J. Hodge, Jim Austin: Hierarchical Growing Cell Structures: TreeGCS. IEEE Trans. Knowl. Data Eng. 13(2): 207-218 (2001)

C. E. Tuke, S. E. M. O'Keefe, Jim Austin: Self-Similar Convolution Image Distribution Histograms as Invariant Identifiers. BMVC 2001: 1-10

Victoria J. Hodge, Jim Austin: An integrated neural IR system. ESANN 2001: 265-270

Amy Metcalfe, Marcy Snitzer, James Austin: Virtual Adaptive Learning Architecture (VALA). ICALT 2001: 7-10

Michael Weeks, Jim Austin, Anthony Moulds, Aaron Turner, Zygmunt Ulanowski, Julian Young: Mapping Correlation Matrix Memory Applications onto a Beowulf Cluster. ICANN 2001: 156-163

Victoria J. Hodge, Jim Austin: A Novel Binary Spell Checker. ICANN 2001: 1199-1204

Stefan Wermter, Jim Austin, David J. Willshaw, Mark Elshaw: Towards Novel Neuroscience-Inspired Computing. Emergent Neural Computational Architectures Based on Neuroscience 2001: 1-19

Daniel Kustrin, Jim Austin: Connectionist Propositional Logic. Emergent Neural Computational Architectures Based on Neuroscience 2001: 534-546

Stefan Wermter, Jim Austin, David J. Willshaw (Eds.): Emergent Neural Computational Architectures Based on Neuroscience - Towards Neuroscience-Inspired Computing. Lecture Notes in Computer Science 2036, Springer 2001, isbn 3-540-42363-X

Brian Drabble, Laurent Chaudron, Catherine Tessier, Sue Abu-Hakima, Steven Willmott, Jim Austin, Boi Faltings, Eugene C. Freuder, Gerhard Friedrich, Alex Alves Freitas, Ulises Cortés, Miquel Sànchez-Marrè, David W. Aha, Irma Becerra-Fernandez, Héctor Muñoz-Avila, Aditya Ghose, Tim Menzies, Ken Satoh, Mary Elaine Califf, Michael T. Cox, Sandip Sen, Patrick Brézillon, Jean-Charles Pomerol, Roy M. Turner, Elise H. Turner: Reports on the AAAI 1999 Workshop Program. AI Magazine 21(1): 95-100 (2000)

Soo-Young Lee, Jim Austin, Rhee Man Kil: Building information systems based on neural networks. Neurocomputing 35(1-4): 1-2 (2000)

Jim Austin, Ken Lees: A search engine based on neural correlation matrix memories. Neurocomputing 35(1-4): 55-72 (2000)

Simon J. Hickinbotham, James Austin: Novelty Detection in Airframe Strain Data. ICPR 2000: 2536-2539

Simon J. Hickinbotham, James Austin: Neural Networks for Novelty Detection in Airframe Strain Data. IJCNN (6) 2000: 375-380

Victoria J. Hodge, Jim Austin: An Evaluation of Standard Retrieval Algorithms and a Weightless Neural Approach. IJCNN (5) 2000: 591-596

Aaron Turner, Jim Austin: Performance evaluation of a fast chemical structure matching method using distributed neural relaxation. KES 2000: 201-204

Victoria J. Hodge, James Austin: Hierarchical growing cell structures: TreeGCS. KES 2000: 553-556

Sujeewa Alwis, Jim Austin: A Neural Network Architecture for Trademark Image Retrieval. IWANN (2) 1999: 361-372

Ping Zhou, Jim Austin, John Kennedy: A Binary Correlation Matrix Memory k-NN Classifier with Hardware Implementation. BMVC 1998: 1-10

Christos Orovas, Jim Austin: A Cellular Neural Associative Array for Symbolic Vision. Hybrid Neural Systems 1998: 372-386

Christos Orovas, James Austin: Cellular Associative Symbolic Processing for Pattern Recognition. MFCS Workshop on Grammar Systems 1998: 269-279

Ping Zhou, Jim Austin, John Kennedy: A High Performance k-NN Classifier Using a Binary Correlation Matrix Memory. NIPS 1998: 713-722

Mick Turner, Jim Austin: Matching performance of binary correlation matrix memories. Neural Networks 10(9): 1637-1648 (1997)

Jim Austin, Giorgio Giacinto, I. Kanellopoulos, Ken Lees, Fabio Roli, Gianni Vernazza, G. Wilkinson: The COMPARES Project: COnnectionist Methods for Preprocessing and Analysis of REmote Sensing Data. ICIAP (2) 1997: 765-772

S. E. M. O'Keefe, Jim Austin: Document Feature Recognition using a Mesh of Associative Memories. BMVC 1996: 1-10

Simon J. Hickinbotham, Edwin R. Hancock, James Austin: Segmenting modulated line textures with S-Gabor filters. ICIP (3) 1996: 149-152

Jim Austin, John Kennedy, Ken Lees: A Neural Architecture for Fast Rule Matching. ANNES 1995: 255-260

S. E. M. O'Keefe, Jim Austin: Application of an Associative Memory to the Analysis of Document Fax Images. BMVC 1994: 1-12

Mick Turner, Jim Austin, Nigel M. Allinson, P. Thompson: Chromosome location and feature extraction using neural networks. Image Vision Comput. 11(4): 235-239 (1993)

Mick Turner, Jim Austin, Nigel M. Allinson, P. Thompson: Matching an Elastic Model of Chromosomal Shape to Features on a Self-Organising Map. BMVC 1993: 1-10

George Bolt, James Austin, Gary Morgan: Uniform tuple storage in ADAM. Pattern Recognition Letters 13(5): 339-344 (1992)

Mick Turner, Jim Austin, Nigel M. Allinson, P. Thompson: A Neural Network Approach to Recognition of Structural Aberrations in Chromosomes. BMVC 1992: 1-9

Jim Austin, B. Nigel Brooke: Investigating Invariant Pattern Recognition Using a Flexible Development Environment. Alvey Vision Conference 1989: 1-4

James Austin: Grey Scale N-Tulpe Processing. Pattern Recognition 1988: 110-119

Jim Austin, T. John Stonham: Distributed associative memory for use in scene analysis. Image Vision Comput. 5(4): 251-260 (1987)