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Institution

The Chinese University of Hong Kong

EducationHong Kong, China
About: The Chinese University of Hong Kong is a education organization based out in Hong Kong, China. It is known for research contribution in the topics: Population & Computer science. The organization has 43411 authors who have published 93672 publications receiving 3066651 citations.
Topics: Population, Computer science, Cancer, Medicine, China


Papers
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Journal ArticleDOI
TL;DR: Based on interviews with 36 venture capitalists in 24 venture capital firms investing in China, this paper found that China's institutional environment creates a number of significant differences from the US and Europe, and discussed the impact of these findings on future research on Asian venture capital, theory development, and the activities of venture capital professionals in that region.

545 citations

Proceedings ArticleDOI
15 Jun 2019
TL;DR: A new neural network for enhancing underexposed photos is presented, which introduces intermediate illumination in its network to associate the input with expected enhancement result, which augments the network's capability to learn complex photographic adjustment from expert-retouched input/output image pairs.
Abstract: This paper presents a new neural network for enhancing underexposed photos. Instead of directly learning an image-to-image mapping as previous work, we introduce intermediate illumination in our network to associate the input with expected enhancement result, which augments the network's capability to learn complex photographic adjustment from expert-retouched input/output image pairs. Based on this model, we formulate a loss function that adopts constraints and priors on the illumination, prepare a new dataset of 3,000 underexposed image pairs, and train the network to effectively learn a rich variety of adjustment for diverse lighting conditions. By these means, our network is able to recover clear details, distinct contrast, and natural color in the enhancement results. We perform extensive experiments on the benchmark MIT-Adobe FiveK dataset and our new dataset, and show that our network is effective to deal with previously challenging images.

543 citations

Journal ArticleDOI
TL;DR: This work reports here on the direct harvesting of visible-to-near-infrared light for chemical reactions by use of plasmonic Au-Pd nanostructures, and compares the effect of joint plasMonic photocatalysis and photothermal conversion with that of sole Photothermal conversion.
Abstract: The efficient use of solar energy has received wide interest due to increasing energy and environmental concerns. A potential means in chemistry is sunlight-driven catalytic reactions. We report here on the direct harvesting of visible-to-near-infrared light for chemical reactions by use of plasmonic Au–Pd nanostructures. The intimate integration of plasmonic Au nanorods with catalytic Pd nanoparticles through seeded growth enabled efficient light harvesting for catalytic reactions on the nanostructures. Upon plasmon excitation, catalytic reactions were induced and accelerated through both plasmonic photocatalysis and photothermal conversion. Under the illumination of an 809 nm laser at 1.68 W, the yield of the Suzuki coupling reaction was ∼2 times that obtained when the reaction was thermally heated to the same temperature. Moreover, the yield was also ∼2 times that obtained from Au–TiOx–Pd nanostructures under the same laser illumination, where a 25-nm-thick TiOx shell was introduced to prevent the phot...

543 citations

Proceedings ArticleDOI
21 Jul 2017
TL;DR: Zhang et al. as mentioned in this paper adopted stacked hourglass networks to generate attention maps from features at multiple resolutions with various semantics, and designed Hourglass Residual Units (HRUs) to increase the receptive field of the network.
Abstract: In this paper, we propose to incorporate convolutional neural networks with a multi-context attention mechanism into an end-to-end framework for human pose estimation. We adopt stacked hourglass networks to generate attention maps from features at multiple resolutions with various semantics. The Conditional Random Field (CRF) is utilized to model the correlations among neighboring regions in the attention map. We further combine the holistic attention model, which focuses on the global consistency of the full human body, and the body part attention model, which focuses on detailed descriptions for different body parts. Hence our model has the ability to focus on different granularity from local salient regions to global semantic consistent spaces. Additionally, we design novel Hourglass Residual Units (HRUs) to increase the receptive field of the network. These units are extensions of residual units with a side branch incorporating filters with larger receptive field, hence features with various scales are learned and combined within the HRUs. The effectiveness of the proposed multi-context attention mechanism and the hourglass residual units is evaluated on two widely used human pose estimation benchmarks. Our approach outperforms all existing methods on both benchmarks over all the body parts. Code has been made publicly available.

543 citations

Journal ArticleDOI
TL;DR: BIS-guided anesthesia reduced anesthetic exposure and decreased the risk of POCD at 3 months after surgery, and for every 1000 elderly patients undergoing major surgery, anesthetic delivery titrated to a range of BIS between 40 and 60 would prevent 23 patients from PocD and 83 patients from delirium.
Abstract: Background:Previous clinical trials and animal experiments have suggested that long-lasting neurotoxicity of general anesthetics may lead to postoperative cognitive dysfunction (POCD). Brain function monitoring such as the bispectral index (BIS) facilitates anesthetic titration and has been shown to

542 citations


Authors

Showing all 43993 results

NameH-indexPapersCitations
Michael Marmot1931147170338
Jing Wang1844046202769
Jiaguo Yu178730113300
Yang Yang1712644153049
Mark Gerstein168751149578
Gang Chen1673372149819
Jun Wang1661093141621
Jean Louis Vincent1611667163721
Wei Zheng1511929120209
Rui Zhang1512625107917
Ben Zhong Tang1492007116294
Kypros H. Nicolaides147130287091
Thomas S. Huang1461299101564
Galen D. Stucky144958101796
Joseph J.Y. Sung142124092035
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023212
2022904
20217,888
20207,245
20195,968
20185,372