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Prof Dr Stefan Wermter
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Cited by
Year
Continual lifelong learning with neural networks: A review
GI Parisi, R Kemker, JL Part, C Kanan, S Wermter
Neural networks 113, 54-71, 2019
21512019
An overview of hybrid neural systems
S Wermter, R Sun
International Workshop on Hybrid Neural Systems, 1-13, 1998
2931998
An analysis of convolutional long short-term memory recurrent neural networks for gesture recognition
E Tsironi, P Barros, C Weber, S Wermter
Neurocomputing 268, 76-86, 2017
2162017
Hybrid neural systems: from simple coupling to fully integrated neural networks
K McGarry, S Wermter, J MacIntyre
Neural Computing Surveys 2 (1), 62-93, 1999
1611999
Face expression recognition with a 2-channel convolutional neural network
D Hamester, P Barros, S Wermter
2015 International Joint Conference on Neural Networks (IJCNN), 1787-1794, 2015
1412015
Lifelong learning of spatiotemporal representations with dual-memory recurrent self-organization
GI Parisi, J Tani, C Weber, S Wermter
Frontiers in neurorobotics 12 (Article 78), 2018
1342018
Speeding up the hyperparameter optimization of deep convolutional neural networks
T Hinz, N Navarro-Guerrero, S Magg, S Wermter
International Journal of Computational Intelligence and Applications 17 (02†…, 2018
1262018
Semantic object accuracy for generative text-to-image synthesis
T Hinz, S Heinrich, S Wermter
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (3), 1552-1565, 2022
1222022
Socially assistive robots: a comprehensive approach to extending independent living
DO Johnson, RH Cuijpers, JF Juola, E Torta, M Simonov, A Frisiello, ...
International Journal of Social Robotics 6 (2), 195-211, 2014
1162014
Efficient facial feature learning with wide ensemble-based convolutional neural networks
H Siqueira, S Magg, S Wermter
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5800-5809, 2020
1152020
Lifelong learning of human actions with deep neural network self-organization
GI Parisi, J Tani, C Weber, S Wermter
Neural Networks 96, 137-149, 2017
1152017
Hybrid connectionist natural language processing
S Wermter
Chapman & Hall, 1995
1111995
Improved techniques for training single-image gans
T Hinz, M Fisher, O Wang, S Wermter
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer†…, 2021
1042021
Connectionist, statistical and symbolic approaches to learning for natural language processing
S Wermter, E Riloff, G Scheler
Springer, 1996
1041996
Developing crossmodal expression recognition based on a deep neural model
P Barros, S Wermter
Adaptive behavior 24 (5), 373-396, 2016
1022016
Generating multiple objects at spatially distinct locations
T Hinz, S Heinrich, S Wermter
arXiv preprint arXiv:1901.00686, 2019
1012019
Self-organizing neural integration of pose-motion features for human action recognition
GI Parisi, C Weber, S Wermter
Frontiers in Neurorobotics 9, 3, 2015
972015
Multimodal emotional state recognition using sequence-dependent deep hierarchical features
P Barros, D Jirak, C Weber, S Wermter
Neural Networks 72, 140-151, 2015
952015
Data mining using rule extraction from Kohonen self-organising maps
J Malone, K McGarry, S Wermter, C Bowerman
Neural Computing & Applications 15, 9-17, 2006
952006
Emotion-modulated attention improves expression recognition: A deep learning model
P Barros, GI Parisi, C Weber, S Wermter
Neurocomputing 253, 104-114, 2017
922017
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Articles 1–20