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Institution

Wuhan University

EducationWuhan, China
About: Wuhan University is a education organization based out in Wuhan, China. It is known for research contribution in the topics: Population & Feature extraction. The organization has 92849 authors who have published 92882 publications receiving 1691049 citations. The organization is also known as: WHU & Wuhan College.


Papers
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Journal ArticleDOI
TL;DR: This paper proposes a simple yet surprisingly effective approach, termed as guided locality preserving matching, for robust feature matching of remote sensing images, and formulate it into a mathematical model, and derive a simple closed-form solution with linearithmic time and linear space complexities.
Abstract: Feature matching, which refers to establishing reliable correspondences between two sets of feature points, is a critical prerequisite in feature-based image registration. This paper proposes a simple yet surprisingly effective approach, termed as guided locality preserving matching, for robust feature matching of remote sensing images. The key idea of our approach is merely to preserve the neighborhood structures of potential true matches between two images. We formulate it into a mathematical model, and derive a simple closed-form solution with linearithmic time and linear space complexities. This enables our method to accomplish the mismatch removal from thousands of putative correspondences in only a few milliseconds. To handle extremely large proportions of outliers, we further design a guided matching strategy based on the proposed method, using the matching result on a small putative set with a high inlier ratio to guide the matching on a large putative set. This strategy can also significantly boost the true matches without sacrifice in accuracy. Experiments on various real remote sensing image pairs demonstrate the generality of our method for handling both rigid and nonrigid image deformations, and it is more than two orders of magnitude faster than the state-of-the-art methods with better accuracy, making it practical for real-time applications.

243 citations

Journal ArticleDOI
Yan-Jun Hu1, Yi Liu1, Xuesong Shen, Xian-Yang Fang1, Song-Sheng Qu1 
TL;DR: In this paper, the interaction between 1-hexylcarbamoyl-5-fluorouracil (Carmofur) and bovine serum albumin (BSA) was studied by spectroscopic methods including fluorescence spectroscopy, circular dichroism (CD) and UV-Visible absorption spectrum.

243 citations

Journal ArticleDOI
Wu Xiaoqun1, Lu Jun-An1
TL;DR: In this paper, an effective observer is designed to identify the unknown parameter of Lu system, then the backstepping method is applied to control the uncertain Lu system to bounded points.
Abstract: Backstepping design is proposed for controlling uncertain Lu system based on parameter identification. Firstly, an effective observer is designed to identify the unknown parameter of Lu system, then the backstepping method is applied to control the uncertain Lu system to bounded points. Furthermore, it can track any continuous or discrete target. Especially, the control law designed here avoids the divergence of 1/ x and 1/ x 2 in Ref. [Chaos, Solitons & Fractals 15 (2003) 897]. Finally numerical simulations are provided to show the effectiveness and feasibility of the developed design method.

242 citations

Journal ArticleDOI
TL;DR: This paper proposes two multitemporal dictionary learning algorithms, expanding on their KSVD and Bayesian counterparts, to make better use of the temporal correlations of quantitative data contaminated by thick clouds and shadows.
Abstract: With regard to quantitative remote sensing products in the visible and infrared ranges, thick clouds and accompanying shadows are an inevitable source of noise. Due to the absence of adequate supporting information from the data themselves, it is a formidable challenge to accurately restore the surficial information underlying large-scale clouds. In this paper, dictionary learning is expanded into the multitemporal recovery of quantitative data contaminated by thick clouds and shadows. This paper proposes two multitemporal dictionary learning algorithms, expanding on their KSVD and Bayesian counterparts. In order to make better use of the temporal correlations, the expanded KSVD algorithm seeks an optimized temporal path, and the expanded Bayesian method adaptively weights the temporal correlations. In the experiments, the proposed algorithms are applied to a reflectance product and a land surface temperature product, and the respective advantages of the two algorithms are investigated. The results show that, from both the qualitative visual effect and the quantitative objective evaluation, the proposed methods are effective.

242 citations

Journal ArticleDOI
TL;DR: The results suggest that the growth of Cs2 AgBiBr6 under Br-poor/Bi-rich conditions is preferred for suppressing the formation of the deep defects, which is beneficial for maximizing the photovoltaic performance.
Abstract: Bismuth- or antimony-based lead-free double perovskites represented by Cs2 AgBiBr6 have recently been considered promising alternatives to the emerging lead-based perovskites for solar cell applications. These new perovskites belong to the Fm3‾ m space group and consist of two types of octahedra alternating in a rock-salt face-centered cubic structure. We show, by density functional theory calculations, that the stable chemical potential region for pure Cs2 AgBiBr6 is narrow. Ag vacancies are a shallow accepters and can easily form, leading to intrinsic p-type conductivity. Bi vacancies and AgBi antisites are deep acceptors and should be the dominant defects under the Br-rich growth conditions. Our results suggest that the growth of Cs2 AgBiBr6 under Br-poor/Bi-rich conditions is preferred for suppressing the formation of the deep defects, which is beneficial for maximizing the photovoltaic performance.

241 citations


Authors

Showing all 93441 results

NameH-indexPapersCitations
Jing Wang1844046202769
Jiaguo Yu178730113300
Lei Jiang1702244135205
Gang Chen1673372149819
Omar M. Yaghi165459163918
Xiang Zhang1541733117576
Yi Yang143245692268
Thomas P. Russell141101280055
Jun Chen136185677368
Lei Zhang135224099365
Chuan He13058466438
Han Zhang13097058863
Lei Zhang130231286950
Zhen Li127171271351
Chao Zhang127311984711
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023286
20221,139
20219,716
20209,672
20197,977
20186,629