Sheila Garfield
Sheila Garfield
Verified email at sunderland.ac.uk
TitleCited byYear
Recent trends in knowledge and data integration for the life sciences
K McGarry, S Garfield, N Morris
Expert Systems 23 (5), 330-341, 2006
182006
Call classification using recurrent neural networks, support vector machines and finite state automata
S Garfield, S Wermter
Knowledge and Information Systems 9 (2), 131-156, 2006
152006
Auto-extraction, representation and integration of a diabetes ontology using Bayesian networks
K McGarry, S Garfield, S Wermter
Twentieth IEEE International Symposium on Computer-Based Medical Systems …, 2007
132007
Self-Organising Networks for Classification Learning from Normal and Aphasic Speech
S Garfield, M Elshaw, S Wermter
Proceedings of the 23d Conference of the Cognitive Science Society …, 2001
102001
The development of an advanced maintenance training programme utilizing augmented reality
V Simon, D Baglee, S Garfield, D Galar
72014
Recurrent neural learning for helpdesk call routing
S Garfield, S Wermter
International Conference on Artificial Neural Networks, 296-301, 2002
62002
Integration of hybrid bio-ontologies using Bayesian networks for knowledge discovery
K McGarry, S Garfield, N Morris, S Wermter
Proceedings of the 3rd International Conference on Neural-Symbolic Learning …, 2007
52007
Spoken language classification using hybrid classifier combination
S Garfield, S Wermter, S Devlin
International Journal of Hybrid Intelligent Systems 2 (1), 13-33, 2005
52005
Comparing support vector machines, recurrent networks, and finite state transducers for classifying spoken utterances
S Garfield, S Wermter
Artificial Neural Networks and Neural Information Processing—ICANN/ICONIP …, 2003
52003
CERIF for Datasets (C4D)–An Overview
K Ginty, S Kerridge, P Fairley, R Henderson, P Cranner, A Bokma, ...
euroCRIS, 2012
42012
Cerif4Datasets (C4D)–Utilising Semantics for the Discovery and Exploration of Datasets in Research
A Bokma, S Garfield, D Nelson, E Omran, O Corcho
euroCRIS, 2012
32012
Recurrent Neural Learning for Classifying Spoken Utterances
S Garfield, S Wermter
Expert Update, Special Issue on Neural Language Processing 6 (3), 31-36, 2003
32003
Automated representation of non-emotional expressivity to facilitate understanding of facial mobility: Preliminary findings
K Clawson, LS Delicato, S Garfield, S Young
2017 Intelligent Systems Conference (IntelliSys), 779-785, 2017
22017
POSTER: CERIFFORDATASETS
K Ginty, S Kerridge, P Fairley, R Henderson, P Cranner, A Bokma, ...
2012
CERIF for Datasets (C4D)
K Ginty, S Kerridge, P Fairley, R Henderson, P Cranner, A Bokma, ...
2012
Article _
K McGarry, S Garfield, N Morris
Expert Systems 23 (5), 331, 2006
2006
Hybrid Processing for Spoken Language Classification
S Garfield
University of Sunderland, 2004
2004
Intelligent and Hybrid Systems-Comparing Support Vector Machines, Recurrent Networks, and Finite State Transducers for Classifying Spoken Utterances
S Garfield, S Wermter
Lecture Notes in Computer Science 2714, 646-653, 2003
2003
Review of: Speech and language processing
S Garfield
Cognitive Systems Research 2 (2), 167-172, 2001
2001
Automated Representation of NonEmotional Expressivity to Facilitate Understanding of Facial Mobility: Preliminary Findings. In: Intelligent Systems Conference 2017, 7 8 …
K Clawson, L Delicato, S Garfield, S Young
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Articles 1–20