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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: The challenges of using deep learning for remote-sensing data analysis are analyzed, recent advances are reviewed, and resources are provided that hope will make deep learning in remote sensing seem ridiculously simple.
Abstract: Central to the looming paradigm shift toward data-intensive science, machine-learning techniques are becoming increasingly important. In particular, deep learning has proven to be both a major breakthrough and an extremely powerful tool in many fields. Shall we embrace deep learning as the key to everything? Or should we resist a black-box solution? These are controversial issues within the remote-sensing community. In this article, we analyze the challenges of using deep learning for remote-sensing data analysis, review recent advances, and provide resources we hope will make deep learning in remote sensing seem ridiculously simple. More importantly, we encourage remote-sensing scientists to bring their expertise into deep learning and use it as an implicit general model to tackle unprecedented, large-scale, influential challenges, such as climate change and urbanization.

2,095 citations

Journal ArticleDOI
04 Mar 1999-Nature
TL;DR: In this article, a class of π;-conjugated compounds that exhibit large δ (as high as 1, 250 × 10−50 cm4 s per photon) and enhanced two-photon sensitivity relative to ultraviolet initiators were developed and used to demonstrate a scheme for three-dimensional data storage which permits fluorescent and refractive readout, and the fabrication of threedimensional micro-optical and micromechanical structures, including photonic bandgap-type structures.
Abstract: Two-photon excitation provides a means of activating chemical or physical processes with high spatial resolution in three dimensions and has made possible the development of three-dimensional fluorescence imaging1, optical data storage2,3 and lithographic microfabrication4,5,6. These applications take advantage of the fact that the two-photon absorption probability depends quadratically on intensity, so under tight-focusing conditions, the absorption is confined at the focus to a volume of order λ3 (where λ is the laser wavelength). Any subsequent process, such as fluorescence or a photoinduced chemical reaction, is also localized in this small volume. Although three-dimensional data storage and microfabrication have been illustrated using two-photon-initiated polymerization of resins incorporating conventional ultraviolet-absorbing initiators, such photopolymer systems exhibit low photosensitivity as the initiators have small two-photon absorption cross-sections (δ). Consequently, this approach requires high laser power, and its widespread use remains impractical. Here we report on a class of π;-conjugated compounds that exhibit large δ (as high as 1, 250 × 10−50 cm4 s per photon) and enhanced two-photon sensitivity relative to ultraviolet initiators. Two-photon excitable resins based on these new initiators have been developed and used to demonstrate a scheme for three-dimensional data storage which permits fluorescent and refractive read-out, and the fabrication of three-dimensional micro-optical and micromechanical structures, including photonic-bandgap-type structures7.

1,975 citations

Journal ArticleDOI
TL;DR: This paper presents a new approach to drug design called “combinatorial biosynthesis and drug discovery through nanofiltration”, which combines the efforts of a single investigator with those of a number of other scientists.
Abstract: Multicomponent reactions (MCRs) are one-pot reactions employing more than two starting materials, e.g. 3, 4, … 7, where most of the atoms of the starting materials are incorporated in the final product.1 Several descriptive tags are regularly attached to MCRs (Fig. 1): they are atom economic, e.g. the majority if not all of the atoms of the starting materials are incorporated in the product; they are efficient, e.g. they efficiently yield the product since the product is formed in one-step instead of multiple sequential steps; they are convergent, e.g. several starting materials combine in one reaction to form the product; they exhibit a very high bond-forming-index (BFI), e.g. several non-hydrogen atom bonds are formed in one synthetic transformation.2 Therefore MCRs are often a useful alternative to sequential multistep synthesis. Open in a separate window Figure 1 Above: multistep syntheses can be divergent (sequential) or convergent; below: in analogy MCR reactions are convergent and one or two component reactions are divergent or less convergent.

1,840 citations

Journal ArticleDOI
TL;DR: The problems and major challenges, along with the directions for the synthesis and surface functionalization of iron oxide NPs, are considered and some future trends and prospective in these research areas are also discussed.
Abstract: Surface functionalized magnetic iron oxide nanoparticles (NPs) are a kind of novel functional materials, which have been widely used in the biotechnology and catalysis. This review focuses on the recent development and various strategies in preparation, structure, and magnetic properties of naked and surface functionalized iron oxide NPs and their corresponding application briefly. In order to implement the practical application, the particles must have combined properties of high magnetic saturation, stability, biocompatibility, and interactive functions at the surface. Moreover, the surface of iron oxide NPs could be modified by organic materials or inorganic materials, such as polymers, biomolecules, silica, metals, etc. The problems and major challenges, along with the directions for the synthesis and surface functionalization of iron oxide NPs, are considered. Finally, some future trends and prospective in these research areas are also discussed.

1,827 citations

Journal ArticleDOI
TL;DR: This rapid advice guideline is suitable for the first frontline doctors and nurses, managers of hospitals and healthcare sections, community residents, public health persons, relevant researchers, and all person who are interested in the 2019-nCoV.
Abstract: In December 2019, a new type viral pneumonia cases occurred in Wuhan, Hubei Province; and then named “2019 novel coronavirus (2019-nCoV)” by the World Health Organization (WHO) on 12 January 2020. For it is a never been experienced respiratory disease before and with infection ability widely and quickly, it attracted the world’s attention but without treatment and control manual. For the request from frontline clinicians and public health professionals of 2019-nCoV infected pneumonia management, an evidence-based guideline urgently needs to be developed. Therefore, we drafted this guideline according to the rapid advice guidelines methodology and general rules of WHO guideline development; we also added the first-hand management data of Zhongnan Hospital of Wuhan University. This guideline includes the guideline methodology, epidemiological characteristics, disease screening and population prevention, diagnosis, treatment and control (including traditional Chinese Medicine), nosocomial infection prevention and control, and disease nursing of the 2019-nCoV. Moreover, we also provide a whole process of a successful treatment case of the severe 2019-nCoV infected pneumonia and experience and lessons of hospital rescue for 2019-nCoV infections. This rapid advice guideline is suitable for the first frontline doctors and nurses, managers of hospitals and healthcare sections, community residents, public health persons, relevant researchers, and all person who are interested in the 2019-nCoV.

1,783 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