Jianwei Zhang
University of Hamburg
756 Papers
2.6K Citations
Jianwei Zhang is an academic researcher from University of Hamburg. The author has contributed to research in topics: Computer science & Robot. The author has an hindex of 39, co-authored 607 publications. Previous affiliations of Jianwei Zhang include Bielefeld University & Tsinghua University.
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Papers
Robot Automation of Sampling and Sample Management during Cultivation of Mammalian Cells in Pilot Scale
Dirk Lütkemeyer,Iris Poggendorf,Thomas Scherer,Jianwei Zhang,Alois Knoll,Jürgen Lehmann +5 more
- 01 Jan 2001
TL;DR: A new device is developed which fulfils the need to be steam sterilizable for an application in industrial production environment and information for optimisation of feed and harvest strategies can be retrieved from the analysed parameters additionally.
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Neuro-Fuzzy Modelling of Time Series
Jianwei Zhang,Alois Knoll +1 more
- 01 Jan 2001
TL;DR: This paper proposes an approach for the multivariate modelling of time series with neuro-fuzzy systems based on adaptive B-splines which can approximate any given input-output data series of low dimension.
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Design and implementation of a complex agent using DFA for the MPR vision system
Weiwei Lu,Liwei Zhang,Zhong Wan,Ying Hu,Jianwei Zhang +4 more
- 07 Oct 2010
TL;DR: The complex agent using Deterministic Finite Automaton (DFA) is expanded from the wheeled mobile robot to a MPR successfully, and the monocular vision part is improved to stereo vision.
2
Modeling and simulation of porpoising for a multilink dolphin robot
Yujia Wang,Junzhi Yu,Jianwei Zhang +2 more
- 01 Dec 2011
TL;DR: This paper analytically analyzes the porpoising behavior of dolphins and other cetaceans in the context of bio-robotics and suggests that the route diversion action results in a significant speed increase while porpoise.
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A comprehensive social matrix factorization for recommendations with prediction and feedback mechanisms by fusing trust relationships and social tags
TL;DR: A social recommendation method incorporating trust relationships and social tags is proposed, which obtains user similarity and item similarity through potential feature vectors of users and items, and continuously trains them to obtain accurate similarity relationships to improve recommendation performance.
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