Institution
Nanjing University
Education•Nanjing, China•
About: Nanjing University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Catalysis & Adsorption. The organization has 85961 authors who have published 105504 publications receiving 2289036 citations. The organization is also known as: NJU & Nanking University.
Topics: Catalysis, Adsorption, Population, Computer science, Thin film
Papers published on a yearly basis
Papers
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TL;DR: Zhang et al. as mentioned in this paper proposed a multi-label classification model based on Graph Convolutional Network (GCN), where each node (label) is represented by word embeddings of a label, and GCN is learned to map this label graph into a set of inter-dependent object classifiers.
Abstract: The task of multi-label image recognition is to predict a set of object labels that present in an image. As objects normally co-occur in an image, it is desirable to model the label dependencies to improve the recognition performance. To capture and explore such important dependencies, we propose a multi-label classification model based on Graph Convolutional Network (GCN). The model builds a directed graph over the object labels, where each node (label) is represented by word embeddings of a label, and GCN is learned to map this label graph into a set of inter-dependent object classifiers. These classifiers are applied to the image descriptors extracted by another sub-net, enabling the whole network to be end-to-end trainable. Furthermore, we propose a novel re-weighted scheme to create an effective label correlation matrix to guide information propagation among the nodes in GCN. Experiments on two multi-label image recognition datasets show that our approach obviously outperforms other existing state-of-the-art methods. In addition, visualization analyses reveal that the classifiers learned by our model maintain meaningful semantic topology.
433 citations
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TL;DR: In this paper, the authors demonstrated that careful structural designs can exploit environmental energy to enhance the performance of an interfacial solar vapor generation device to well above the theoretical limit of vapor output, assuming 100% solar-to-vapor energy transfer efficiency, under various light intensities.
433 citations
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TL;DR: The prepared GNS-PEG-Ce6 shows excellent water dispersibility, good biocompatibility, enhanced cellular uptake and remarkable anticancer efficiency upon irradiation in vivo.
Abstract: Chlorin e6 conjugated gold nanostars (GNS-PEG-Ce6) are used to perform simultaneous photodynamic/plasmonic photothermal therapy (PDT/PPTT) upon single laser irradiation. The early-phase PDT effect is coordinated with the late-phase PPTT effect to obtain synergistic anticancer efficiency. The prepared GNS-PEG-Ce6 shows excellent water dispersibility, good biocompatibility, enhanced cellular uptake and remarkable anticancer efficiency upon irradiation in vivo.
432 citations
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TL;DR: The findings underlined the high potential ecological risks of FPs, and suggested that NPs should be given more concerns, in terms of their interaction with hydrophobic pollutants in the environment.
432 citations
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TL;DR: Wang et al. as mentioned in this paper conducted an eco-efficiency analysis for regional industrial systems in China by developing data envelopment analysis (DEA) based models, which showed that Tianjing, Shanghai, Guangdong, Beijing, Hainan and Qinghai are relatively eco-efficient.
431 citations
Authors
Showing all 86514 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yi Chen | 217 | 4342 | 293080 |
H. S. Chen | 179 | 2401 | 178529 |
Zhenan Bao | 169 | 865 | 106571 |
Gang Chen | 167 | 3372 | 149819 |
Peter G. Schultz | 156 | 893 | 89716 |
Xiang Zhang | 154 | 1733 | 117576 |
Rui Zhang | 151 | 2625 | 107917 |
Yi Yang | 143 | 2456 | 92268 |
Markku Kulmala | 142 | 1487 | 85179 |
Jian Yang | 142 | 1818 | 111166 |
Wei Huang | 139 | 2417 | 93522 |
Bin Liu | 138 | 2181 | 87085 |
Jun Lu | 135 | 1526 | 99767 |
Hui Li | 135 | 2982 | 105903 |
Lei Zhang | 135 | 2240 | 99365 |