Institution
Beihang University
Education•Beijing, 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.
Topics: Control theory, Microstructure, Nonlinear system, Artificial neural network, Feature extraction
Papers published on a yearly basis
Papers
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TL;DR: Both theoretical analysis and experimental results prove that the proposed gradient domain GIF can produce better resultant images, especially near the edges, where halos appear in the original GIF.
Abstract: Guided image filter (GIF) is a well-known local filter for its edge-preserving property and low computational complexity. Unfortunately, the GIF may suffer from halo artifacts, because the local linear model used in the GIF cannot represent the image well near some edges. In this paper, a gradient domain GIF is proposed by incorporating an explicit first-order edge-aware constraint. The edge-aware constraint makes edges be preserved better. To illustrate the efficiency of the proposed filter, the proposed gradient domain GIF is applied for single-image detail enhancement, tone mapping of high dynamic range images and image saliency detection. Both theoretical analysis and experimental results prove that the proposed gradient domain GIF can produce better resultant images, especially near the edges, where halos appear in the original GIF.
225 citations
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TL;DR: This paper presents the probabilistic approach to reconstruction and discusses its optimality and robustness, and develops the asymptotic analysis of the corresponding phase diagrams with and without measurement noise.
Abstract: Compressed sensing is a signal processing method that acquires data directly in a compressed form This allows one to make less measurements than what was considered necessary to record a signal, enabling faster or more precise measurement protocols in a wide range of applications Using an interdisciplinary approach, we have recently proposed in [arXiv:11094424] a strategy that allows compressed sensing to be performed at acquisition rates approaching to the theoretical optimal limits In this paper, we give a more thorough presentation of our approach, and introduce many new results We present the probabilistic approach to reconstruction and discuss its optimality and robustness We detail the derivation of the message passing algorithm for reconstruction and expectation max- imization learning of signal-model parameters We further develop the asymptotic analysis of the corresponding phase diagrams with and without measurement noise, for different distribution of signals, and discuss the best possible reconstruction performances regardless of the algorithm We also present new efficient seeding matrices, test them on synthetic data and analyze their performance asymptotically
224 citations
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TL;DR: The development and application of superoleophobic surfaces have aroused worldwide interest during the past few years as mentioned in this paper. But the development of these surfaces are not only for fundamental research but also for various practical applications in self-cleaning, oil-repellent coatings, and antibioadhesion.
Abstract: The construction and application of superoleophobic surfaces have aroused worldwide interest during the past few years. These surfaces are of great significance not only for fundamental research but also for various practical applications in self-cleaning, oil-repellent coatings, and antibioadhesion. The unique properties of polymers have made them one of the most important materials for constructing superoleophobic materials. This article reviews recent developments in the design, fabrication, and application of polymeric superoleophobic surfaces. © 2012 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys, 2012
224 citations
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TL;DR: The observation of new properties of secondary cosmic rays Li, Be, and B measured in the rigidity range 1.9 GV to 3.3 TV with a total of 5.4×10^{6} nuclei collected by AMS during the first five years of operation aboard the International Space Station is reported.
Abstract: We report on the observation of new properties of secondary cosmic rays Li, Be, and B measured in the rigidity (momentum per unit charge) range 1.9 GV to 3.3 TV with a total of 5.4×10^{6} nuclei collected by AMS during the first five years of operation aboard the International Space Station. The Li and B fluxes have an identical rigidity dependence above 7 GV and all three fluxes have an identical rigidity dependence above 30 GV with the Li/Be flux ratio of 2.0±0.1. The three fluxes deviate from a single power law above 200 GV in an identical way. This behavior of secondary cosmic rays has also been observed in the AMS measurement of primary cosmic rays He, C, and O but the rigidity dependences of primary cosmic rays and of secondary cosmic rays are distinctly different. In particular, above 200 GV, the secondary cosmic rays harden more than the primary cosmic rays.
224 citations
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TL;DR: A simple enantioselective sensing device based on a single artificial β-cyclodextrin-modified nanochannel system shows highly selective recognition of histidine enantiomers through monitoring of ionic current signatures.
Abstract: Efficient enantiomer discrimination with a convenient system remains a challenge in the fields of biochemistry, medical science, and pharmaceutics. Here we report a simple enantioselective sensing device based on a single artificial β-cyclodextrin-modified nanochannel system. This nanodevice shows highly selective recognition of histidine enantiomers through monitoring of ionic current signatures.
223 citations
Authors
Showing all 67500 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yi Chen | 217 | 4342 | 293080 |
H. S. Chen | 179 | 2401 | 178529 |
Alan J. Heeger | 171 | 913 | 147492 |
Lei Jiang | 170 | 2244 | 135205 |
Wei Li | 158 | 1855 | 124748 |
Shu-Hong Yu | 144 | 799 | 70853 |
Jian Zhou | 128 | 3007 | 91402 |
Chao Zhang | 127 | 3119 | 84711 |
Igor Katkov | 125 | 972 | 71845 |
Tao Zhang | 123 | 2772 | 83866 |
Nicholas A. Kotov | 123 | 574 | 55210 |
Shi Xue Dou | 122 | 2028 | 74031 |
Li Yuan | 121 | 948 | 67074 |
Robert O. Ritchie | 120 | 659 | 54692 |
Haiyan Wang | 119 | 1674 | 86091 |