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
Learning Local Planners for Human-aware Navigation in Indoor Environments
Ronja Guldenring,Michael Görner,Norman Hendrich,Niels Jul Jacobsen,Jianwei Zhang +4 more
- 24 Oct 2020
TL;DR: In this paper, the authors present a system to train neural-network policies for a local planner component, explicitly accounting for humans navigating the space, which can be deployed as a drop-in replacement for other local planners and significantly improve on traditional implementations.
Fertilization shapes a well-organized community of bacterial decomposers for accelerated paddy straw degradation.
Yushan Zhan,Wenjing Liu,Yuanyuan Bao,Jianwei Zhang,Evangelos Petropoulos,Zhongpei Li,Xiangui Lin,Youzhi Feng +7 more
TL;DR: Findings indicate that fertilization shapes a well-organized community of decomposers for accelerated straw degradation, and shifted the hub species towards those of high degrading potential and created a more stable and efficient microbial consortium.
Robust High Accuracy Visual-Inertial-Laser SLAM System
Wang Zengyuan,Jianhua Zhang,Shengyong Chen,Conger Yuan,Jingqian Zhang,Jianwei Zhang +5 more
- 01 Nov 2019
TL;DR: A robust and high-accuracy visual-inertial-laser SLAM system that enables modules to be adjusted automatically and flexibly and achieves superior accuracy against other state-of-the-art algorithms.
Unsupervised Multi-document Summarization with Holistic Inference
Haopeng Zhang,Sangwoo Cho,Kaiqiang Song,Xiaoyang Wang,Hongwei Wang,Jianwei Zhang,Dong-Han Yu +6 more
TL;DR: This paper proposes a new holistic framework for unsupervised multi-document extractive summarization that incorporates the holistic beam search inference method associated with the holistic measurements, named Subset Representative Index (SRI).
A Novel Correction for the Adjusted Box-Pierce Test
TL;DR: A further correction to the adjusted Box-Pierce test that possesses near perfect type I error rates is proposed, based on an inflation of the rejection region for all sample sizes and lags calculated via a linear model applied to simulated data that encompasses a large range of data scenarios.