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Institution

Beihang University

EducationBeijing, China
About: Beihang University is a education organization based out in Beijing, China. It is known for research contribution in the topics: Control theory & Microstructure. The organization has 67002 authors who have published 73507 publications receiving 975691 citations. The organization is also known as: Beijing University of Aeronautics and Astronautics.


Papers
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Proceedings ArticleDOI
14 Jun 2020
TL;DR: Focal Convolution Layer, a new applying of convolution, is presented to enhance the fine-grained learning of the part-level spatial features and the Micro-motion Capture Module is proposed, which is a novel way of temporal modeling for gait task, which focuses on the short-range temporal features rather than the redundant long-range features for cycle gait.
Abstract: Gait recognition, applied to identify individual walking patterns in a long-distance, is one of the most promising video-based biometric technologies. At present, most gait recognition methods take the whole human body as a unit to establish the spatio-temporal representations. However, we have observed that different parts of human body possess evidently various visual appearances and movement patterns during walking. In the latest literature, employing partial features for human body description has been verified being beneficial to individual recognition. Taken above insights together, we assume that each part of human body needs its own spatio-temporal expression. Then, we propose a novel part-based model GaitPart and get two aspects effect of boosting the performance: On the one hand, Focal Convolution Layer, a new applying of convolution, is presented to enhance the fine-grained learning of the part-level spatial features. On the other hand, the Micro-motion Capture Module (MCM) is proposed and there are several parallel MCMs in the GaitPart corresponding to the pre-defined parts of the human body, respectively. It is worth mentioning that the MCM is a novel way of temporal modeling for gait task, which focuses on the short-range temporal features rather than the redundant long-range features for cycle gait. Experiments on two of the most popular public datasets, CASIA-B and OU-MVLP, richly exemplified that our method meets a new state-of-the-art on multiple standard benchmarks. The source code will be available on https://github.com/ChaoFan96/GaitPart.

222 citations

Journal ArticleDOI
TL;DR: This work reviews the experimental and theoretical progress in this field and reports on the discovery of two narrow charm-strange states and more excited heavy hadrons reported in 2003.
Abstract: Since the discovery of the first charmed meson in 1976, many open-charm and open-bottom hadrons were observed. In 2003 two narrow charm-strange states [Formula: see text] and D s1(2460) were discovered by the BaBar and CLEO Collaborations, respectively. After that, more excited heavy hadrons were reported. In this work, we review the experimental and theoretical progress in this field.

222 citations

Journal ArticleDOI
TL;DR: In this article, an artificial fog collector on a large scale is first fabricated through integrating cactus spine-like hydrophobic conical micro-tip arrays with the hydrophilic cotton matrix.
Abstract: Although clean drinking water is a basic human need, freshwater scarcity has been identified as a major global problem of the 21st century. Nature has long served as a source of inspiration for human beings to develop new technology. The cactus in the desert possesses a multifunctional integrated fog collection system originating from the cooperation of a Laplace pressure gradient and the wettability difference. In this contribution, inspired by the cactus, an artificial fog collector on a large scale is first fabricated through integrating cactus spine-like hydrophobic conical micro-tip arrays with the hydrophilic cotton matrix. The novel cactus-inspired fog collector can spontaneously and continuously collect, transport, and preserve fog water, demonstrating high fog collection efficiency and promising applications in the regions with drinking water scarcity. Furthermore, the present approach is simple, time-saving and cost-effective, which provides a potential device and new idea to solve the global water crisis.

222 citations

Journal ArticleDOI
TL;DR: This review summarizes the various treatment methods applied to the removal of heavy metal complexes, with a summary of the mechanisms of action and recent research progress, and comprehensively analyzes future prospects and developments in methods for removal of chelated heavy metals.

222 citations

Journal ArticleDOI
TL;DR: A new self-powered broadband photodetector was fabricated by coating an n-silicon nanowire (n-Si NW) array with a layer of p-cupric oxide (CuO) nanoflakes through a new simple solution synthesis method, showing excellent rectification characteristics in the dark and distinctive photovoltaic behavior under broadband light illumination.
Abstract: A new self-powered broadband photodetector was fabricated by coating an n-silicon nanowire (n-Si NW) array with a layer of p-cupric oxide (CuO) nanoflakes through a new simple solution synthesis method. The p–n heterojunction shows excellent rectification characteristics in the dark and distinctive photovoltaic behavior under broadband light illumination. The photoresponse of the detector at zero bias voltage shows that this self-powered photodetector is highly sensitive to visible and near-infrared light illuminations, with excellent stability and reproducibility. Ultrafast response rise and recovery times of 60 and 80 μs, respectively, are shown by the CuO based nanophotodetector. In addition, the broadband photodetector can also provide a rapid binary response, with current changing from positive to negative upon illumination under a small bias. The binary response arises from the photovoltaic behavior and the low turn-on voltage of the CuO/Si NW device. These properties make the CuO/Si NW broadband ph...

222 citations


Authors

Showing all 67500 results

NameH-indexPapersCitations
Yi Chen2174342293080
H. S. Chen1792401178529
Alan J. Heeger171913147492
Lei Jiang1702244135205
Wei Li1581855124748
Shu-Hong Yu14479970853
Jian Zhou128300791402
Chao Zhang127311984711
Igor Katkov12597271845
Tao Zhang123277283866
Nicholas A. Kotov12357455210
Shi Xue Dou122202874031
Li Yuan12194867074
Robert O. Ritchie12065954692
Haiyan Wang119167486091
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
2023205
20221,178
20216,767
20206,916
20197,080