Mark Elshaw
Mark Elshaw
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα coventry.ac.uk
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Παρατίθεται από
Παρατίθεται από
Έτος
Towards multimodal neural robot learning
S Wermter, C Weber, M Elshaw, C Panchev, H Erwin, F Pulvermüller
Robotics and Autonomous Systems 47 (2-3), 171-175, 2004
582004
Biomimetic neural learning for intelligent robots: Intelligent systems, cognitive robotics, and neuroscience
S Wermter, G Palm, M Elshaw
Springer, 2005
472005
Stacked deep convolutional auto-encoders for emotion recognition from facial expressions
A Ruiz-Garcia, M Elshaw, A Altahhan, V Palade
2017 International Joint Conference on Neural Networks (IJCNN), 1586-1593, 2017
352017
A hybrid generative and predictive model of the motor cortex
C Weber, S Wermter, M Elshaw
Neural Networks 19 (4), 339-353, 2006
292006
The application of genetic algorithms to sensor parameter selection for multisensor array configuration
P Corcoran, J Anglesea, M Elshaw
Sensors and Actuators A: Physical 76 (1-3), 57-66, 1999
271999
Deep learning for emotion recognition in faces
A Ruiz-Garcia, M Elshaw, A Altahhan, V Palade
International Conference on Artificial Neural Networks, 38-46, 2016
262016
Learning robot actions based on self-organising language memory
S Wermter, M Elshaw
Neural Networks 16 (5-6), 691-699, 2003
252003
Emotional recognition from the speech signal for a virtual education agent
A Tickle, S Raghu, M Elshaw
Journal of Physics: Conference Series 450 (1), 012053, 2013
222013
An associator network approach to robot learning by imitation through vision, motor control and language
M Elshaw, C Weber, A Zochios, S Wermter
2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No …, 2004
202004
Towards novel neuroscience-inspired computing
S Wermter, M Elshaw, J Austin, D Willshaw
Emergent neural computational architectures based on neuroscience, 1-19, 2001
202001
Grounding neural robot language in action
S Wermter, C Weber, M Elshaw, V Gallese, F Pulvermüller
Biomimetic neural learning for intelligent robots, 162-181, 2005
17*2005
A hybrid deep learning neural approach for emotion recognition from facial expressions for socially assistive robots
A Ruiz-Garcia, M Elshaw, A Altahhan, V Palade
Neural Computing and Applications 29 (7), 359-373, 2018
162018
Reinforcement Learning
C Weber, M Elshaw, NM Mayer
BoD–Books on Demand, 2008
152008
Pedestrian and cyclist detection and intent estimation for autonomous vehicles: a survey
S Ahmed, MN Huda, S Rajbhandari, C Saha, M Elshaw, S Kanarachos
Applied Sciences 9 (11), 2335, 2019
132019
Towards integrating learning by demonstration and learning by instruction in a multimodal robot
S Wermter, M Elshaw, C Weber, C Panchev, H Erwin
Proceedings of the IROS-2003 Workshop on Robot Learning by Demonstration, 72-79, 2003
132003
A modular approach to self-organization of robot control based on language instruction
S Wermter, M Elshaw, S Farrand
Connection Science 15 (2-3), 73-94, 2003
132003
Reinforcement learning to support meta-level control in air traffic management
DP Alves, L Weigang, BB Souza, C Weber, M Elshaw, N Mayer
Reinforcement Learning–Theory and Applications, 409-424, 2008
122008
Self-Organising Networks for Classification Learning from Normal and Aphasic Speech
S Garfield, M Elshaw, S Wermter
Proceedings of the Annual Meeting of the Cognitive Science Society 23 (23), 2001
112001
Reinforcement learning: theory and applications
C Weber, M Elshaw, NM Mayer
I-TECH Education and Pub., 2008
102008
Deep learning for illumination invariant facial expression recognition
A Ruiz-Garcia, V Palade, M Elshaw, I Almakky
2018 International Joint Conference on Neural Networks (IJCNN), 1-6, 2018
92018
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