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Institution

Chinese Academy of Sciences

GovernmentBeijing, Beijing, China
About: Chinese Academy of Sciences is a government organization based out in Beijing, Beijing, China. It is known for research contribution in the topics: Catalysis & Population. The organization has 421602 authors who have published 634849 publications receiving 14894293 citations. The organization is also known as: CAS.
Topics: Catalysis, Population, Laser, Adsorption, Graphene


Papers
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Book ChapterDOI
23 Aug 2020
TL;DR: This paper addresses the semantic segmentation problem with a focus on the context aggregation strategy, and presents a simple yet effective approach, object-contextual representations, characterizing a pixel by exploiting the representation of the corresponding object class.
Abstract: In this paper, we study the context aggregation problem in semantic segmentation. Motivated by that the label of a pixel is the category of the object that the pixel belongs to, we present a simple yet effective approach, object-contextual representations, characterizing a pixel by exploiting the representation of the corresponding object class. First, we learn object regions under the supervision of the ground-truth segmentation. Second, we compute the object region representation by aggregating the representations of the pixels lying in the object region. Last, we compute the relation between each pixel and each object region, and augment the representation of each pixel with the object-contextual representation which is a weighted aggregation of all the object region representations. We empirically demonstrate our method achieves competitive performance on various benchmarks: Cityscapes, ADE20K, LIP, PASCAL-Context and COCO-Stuff. Our submission “HRNet + OCR + SegFix” achieves the \({1}^{\mathrm {st}}\) place on the Cityscapes leaderboard by the ECCV 2020 submission deadline. Code is available at: https://git.io/openseg and https://git.io/HRNet.OCR.

952 citations

Journal ArticleDOI
TL;DR: A general image fusion framework by combining MST and SR to simultaneously overcome the inherent defects of both the MST- and SR-based fusion methods is presented and experimental results demonstrate that the proposed fusion framework can obtain state-of-the-art performance.

952 citations

Journal ArticleDOI
10 Apr 2003-Nature
TL;DR: The isolation and characterization of MONOCULM 1 (MOC1), a gene that is important in the control of rice tillering, is reported, which encodes a putative GRAS family nuclear protein that is expressed mainly in the axillary bud and functions to initiate axillary buds and to promote their outgrowth.
Abstract: Tillering in rice (Oryza sativa L.) is an important agronomic trait for grain production, and also a model system for the study of branching in monocotyledonous plants. Rice tiller is a specialized grain-bearing branch that is formed on the unelongated basal internode and grows independently of the mother stem (culm) by means of its own adventitious roots. Rice tillering occurs in a two-stage process: the formation of an axillary bud at each leaf axil and its subsequent outgrowth. Although the morphology and histology and some mutants of rice tillering have been well described, the molecular mechanism of rice tillering remains to be elucidated. Here we report the isolation and characterization of MONOCULM 1 (MOC1), a gene that is important in the control of rice tillering. The moc1 mutant plants have only a main culm without any tillers owing to a defect in the formation of tiller buds. MOC1 encodes a putative GRAS family nuclear protein that is expressed mainly in the axillary buds and functions to initiate axillary buds and to promote their outgrowth.

951 citations

Journal ArticleDOI
TL;DR: In this critical review, recent advances in sub-nanometre sized metal clusters (Au, Ag, Cu, etc.) including the synthetic techniques, structural characterizations, novel physical, chemical and optical properties and their potential applications are discussed in detail.
Abstract: Sub-nanometre sized metal clusters, with dimensions between metal atoms and nanoparticles, have attracted more and more attention due to their unique electronic structures and the subsequent unusual physical and chemical properties. However, the tiny size of the metal clusters brings the difficulty of their synthesis compared to the easier preparation of large nanoparticles. Up to now various synthetic techniques and routes have been successfully applied to the preparation of sub-nanometre clusters. Among the metals, gold clusters, especially the alkanethiolate monolayer protected clusters (MPCs), have been extensively investigated during the past decades. In recent years, silver and copper nanoclusters have also attracted enormous interest mainly due to their excellent photoluminescent properties. Meanwhile, more structural characteristics, particular optical, catalytic, electronic and magnetic properties and the related technical applications of the metal nanoclusters have been discovered in recent years. In this critical review, recent advances in sub-nanometre sized metal clusters (Au, Ag, Cu, etc.) including the synthetic techniques, structural characterizations, novel physical, chemical and optical properties and their potential applications are discussed in detail. We finally give a brief outlook on the future development of metal nanoclusters from the viewpoint of controlled synthesis and their potential applications.

951 citations

Journal ArticleDOI
13 Feb 2014-Cell
TL;DR: By coinjection of Cas9 mRNA and sgRNAs into one-cell-stage embryos, this system successfully achieves precise gene targeting in cynomolgus monkeys and enables simultaneous disruption of two target genes in one step, and no off-target mutagenesis was detected by comprehensive analysis.

950 citations


Authors

Showing all 422053 results

NameH-indexPapersCitations
Frank B. Hu2501675253464
Zhong Lin Wang2452529259003
Yi Chen2174342293080
Jing Wang1844046202769
Peidong Yang183562144351
Xiaohui Fan183878168522
H. S. Chen1792401178529
Douglas Scott1781111185229
Jie Zhang1784857221720
Pulickel M. Ajayan1761223136241
Feng Zhang1721278181865
Andrea Bocci1722402176461
Yang Yang1712644153049
Lei Jiang1702244135205
Yang Gao1682047146301
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023170
20222,918
202159,109
202055,057
201952,186
201846,329