Prof Dr Stefan Wermter

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Citations	14240	9932
h-index	52	41
i10-index	246	157

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Cornelius WeberUniversität HamburgVerified email at informatik.uni-hamburg.de
German I. ParisiIBM watsonxVerified email at ibm.com
Pablo BarrosBrussels Laboratory, Sony CorporationVerified email at sony.com
Sven MaggPostdoctoral Researcher, Universität HamburgVerified email at sven-magg.de
Matthias KerzelResearch Assistant, University of HamburgVerified email at informatik.uni-hamburg.de
Stefan HeinrichAssociate Professor, IT University of CopenhagenVerified email at itu.dk
Erik StrahlUniversität HamburgVerified email at informatik.uni-hamburg.de
Mark ElshawCoventry UniversityVerified email at coventry.ac.uk
Manfred EppeHamburg University of TechnologyVerified email at tuhh.de
Dr. Johannes TwiefelResearch Associate at Knowledge Technology Group, Dept. Computer Science, University of HamburgVerified email at informatik.uni-hamburg.de
Nicolás Navarro-GuerreroL3S Research Center, Leibniz University Hannover, GermanyVerified email at l3s.de
Christo PanchevAssistant Professor, University of WarwickVerified email at warwick.ac.uk
Tobias HinzAdobe ResearchVerified email at adobe.com
Ken McGarryAssociate Professor, School of Computer Science, University of SunderlandVerified email at sunderland.ac.uk
Francisco CruzUNSW SydneyVerified email at unsw.edu.au
Doreen JirakUniversity of AntwerpVerified email at uantwerpen.be
Di Fu, Ph.D. 傅迪Department of Psychology, Unviersity of SurreyVerified email at surrey.ac.uk
Egor LakomkinMeta AIVerified email at fb.com
Muhammad Burhan HafezNew Frontiers Fellow/Lecturer (Assistant Professor), University of SouthamptonVerified email at soton.ac.uk
Henrique SiqueiraBig Data in Manufacturing GmbHVerified email at bigdatainmanufacturing.com

Prof Dr Stefan Wermter

University of Hamburg

Verified email at uni-hamburg.de - Homepage

Artificial Intelligence Neural Networks Robotics Machine Learning Cognitive Systems


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Continual lifelong learning with neural networks: A review GI Parisi, R Kemker, JL Part, C Kanan, S Wermter Neural networks 113, 54-71, 2019	3410	2019
An overview of hybrid neural systems S Wermter, R Sun International Workshop on Hybrid Neural Systems, 1-13, 1998	319	1998
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	273	2017
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	197	2022
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	180	2021
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	171	1999
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	169	2015
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	165	2020
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	164	2018
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	153	2018
Survey on reinforcement learning for language processing V Uc-Cetina, N Navarro-Guerrero, A Martin-Gonzalez, C Weber, ... Artificial Intelligence Review 56 (2), 1543-1575, 2023	146	2023
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	141	2014
The OMG-emotion behavior dataset P Barros, N Churamani, E Lakomkin, H Siqueira, A Sutherland, S Wermter Proceedings of the International Joint Conference on Neural Networks (IJCNN …, 2018	137	2018
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	136	2017
Generating multiple objects at spatially distinct locations T Hinz, S Heinrich, S Wermter arXiv preprint arXiv:1901.00686, 2019	124	2019
Hybrid connectionist natural language processing S Wermter Chapman & Hall, 1995	115	1995
Connectionist, statistical and symbolic approaches to learning for natural language processing S Wermter, E Riloff, G Scheler Springer, 1996	108	1996
Developing crossmodal expression recognition based on a deep neural model P Barros, S Wermter Adaptive behavior 24 (5), 373-396, 2016	107	2016
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	106	2006
Emotion-modulated attention improves expression recognition: A deep learning model P Barros, GI Parisi, C Weber, S Wermter Neurocomputing 253, 104-114, 2017	104	2017

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