Search Results - "Zhu, Guokang"

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  1. 1

    Hyperspectral Band Selection by Multitask Sparsity Pursuit by Yuan, Yuan, Zhu, Guokang, Wang, Qi

    “…Hyperspectral images have been proved to be effective for a wide range of applications; however, the large volume and redundant information also bring a lot of…”
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    Journal Article
  2. 2

    Unsupervised Hyperspectral Band Selection by Dominant Set Extraction by Zhu, Guokang, Huang, Yuancheng, Lei, Jingsheng, Bi, Zhongqin, Xu, Feifei

    “…Unsupervised hyperspectral band selection has been an important topic in hyperspectral imagery. This technique aims at selecting some critical and decisive…”
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    Journal Article
  3. 3

    Fast Hyperspectral Anomaly Detection via High-Order 2-D Crossing Filter by Yuan, Yuan, Wang, Qi, Zhu, Guokang

    “…Anomaly detection has been an important topic in hyperspectral image analysis. This technique is sometimes more preferable than the supervised target detection…”
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    Journal Article
  4. 4

    Hyperspectral Band Selection via Rank Minimization by Zhu, Guokang, Huang, Yuancheng, Li, Shuying, Tang, Jun, Liang, Dong

    Published in IEEE geoscience and remote sensing letters (01-12-2017)
    “…Band selection is an important preprocessing technique for hyperspectral imagery, through which a subset of critical and representative spectral bands can be…”
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    Journal Article
  5. 5

    Learning Saliency by MRF and Differential Threshold by Zhu, Guokang, Wang, Qi, Yuan, Yuan, Yan, Pingkun

    Published in IEEE transactions on cybernetics (01-12-2013)
    “…Saliency detection has been an attractive topic in recent years. The reliable detection of saliency can help a lot of useful processing without prior knowledge…”
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    Journal Article
  6. 6

    SIFT on manifold: An intrinsic description by Zhu, Guokang, Wang, Qi, Yuan, Yuan, Yan, Pingkun

    Published in Neurocomputing (Amsterdam) (03-08-2013)
    “…Scale Invariant Feature Transform is a widely used image descriptor, which is distinctive and robust in real-world applications. However, the high…”
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    Journal Article
  7. 7

    NATAS: Neural Activity Trace Aware Saliency by Zhu, Guokang, Wang, Qi, Yuan, Yuan

    Published in IEEE transactions on cybernetics (01-07-2014)
    “…Saliency detection has raised much interest in computer vision recently. Many visual saliency models have been developed for individual images, video clips,…”
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    Journal Article
  8. 8

    Learning from Large-Scale Wearable Device Data for Predicting the Epidemic Trend of COVID-19 by Zhu, Guokang, Li, Jia, Meng, Zi, Yu, Yi, Li, Yanan, Tang, Xiao, Dong, Yuling, Sun, Guangxin, Zhou, Rui, Wang, Hui, Wang, Kongqiao, Huang, Wang

    Published in Discrete dynamics in nature and society (05-05-2020)
    “…The coronavirus disease 2019 (COVID-19) pandemic has triggered a new response involving public health surveillance. The popularity of personal wearable devices…”
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    Journal Article
  9. 9

    A paralleled CNN and Transformer network for PPG-based cuff-less blood pressure estimation by Tian, Zhonghe, Liu, Aiping, Zhu, Guokang, Chen, Xun

    Published in Biomedical signal processing and control (01-01-2025)
    “…Cuff-less blood pressure measurement plays a pivotal part in hypertension diagnosis and prevention. By employing deep learning algorithms, blood pressure…”
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    Journal Article
  10. 10

    Tag-Saliency: Combining bottom-up and top-down information for saliency detection by Zhu, Guokang, Wang, Qi, Yuan, Yuan

    Published in Computer vision and image understanding (01-01-2014)
    “…•Integrate auto-tagging in saliency detection to label large scale multimedia data.•Combine low-level and high-level information in a uniformed saliency…”
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    Journal Article
  11. 11

    Multi-spectral dataset and its application in saliency detection by Wang, Qi, Zhu, Guokang, Yuan, Yuan

    Published in Computer vision and image understanding (01-12-2013)
    “…•A multi-spectral dataset is constructed containing RGB and near-infrared images.•The incorporation of near-infrared is proved to be valuable for saliency…”
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    Journal Article
  12. 12

    Learning from Large-Scale Wearable Device Data for Predicting Epidemics Trend of COVID-19 by Wang, Hui, Wang, Kongqiao, Huang, Wang, Sun, Guangxin, Dong, Yuling, Tang, Xiao, Li, Yanan, Yu, Yi, Meng, Zi, Li, Jia, Zhu, Guokang, Zhou, Rui

    Published in Discrete dynamics in nature and society (31-05-2020)
    “…The coronavirus disease 2019 (COVID-19) pandemic has triggered a new response involving public health surveillance. The popularity of personal wearable devices…”
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    Journal Article
  13. 13

    Statistical quantization for similarity search by Wang, Qi, Zhu, Guokang, Yuan, Yuan

    Published in Computer vision and image understanding (01-07-2014)
    “…•Formulate a k-means hashing model based on generalized likelihood ratio analysis.•Introduce statistical analysis into the out-of-sample extension of…”
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    Journal Article
  14. 14

    Robust K-means algorithm with automatically splitting and merging clusters and its applications for surveillance data by Lei, Jingsheng, Jiang, Teng, Wu, Kui, Du, Haizhou, Zhu, Guokang, Wang, Zhaoqing

    Published in Multimedia tools and applications (01-10-2016)
    “…With the pervasive of the definition of the smart city, the data volume of the surveillance system, huge number of video surveillance devices is now rapidly…”
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    Journal Article
  15. 15

    A remote sensing image classification method based on sparse representation by Wu, Shulei, Chen, Huandong, Bai, Yong, Zhu, Guokang

    Published in Multimedia tools and applications (01-10-2016)
    “…With the development of remote sensing image applications, sparse-based representation classification approaches have been investigated for better…”
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    Journal Article
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    Probability density function solution to nonlinear ship roll motion excited by external Poisson white noise by Er, GuoKang, Zhu, HaiTao, Iu, VaiPan, Kou, KunPang

    Published in Science China Technological Sciences (01-05-2011)
    “…The stationary probability density function (PDF) solution to nonlinear ship roll motion excited by Poisson white noise is analyzed. Subjected to such random…”
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    Journal Article