Search Results - "Chui, Charles K."

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  1. 1

    Fine Perceptive GANs for Brain MR Image Super-Resolution in Wavelet Domain by You, Senrong, Lei, Baiying, Wang, Shuqiang, Chui, Charles K., Cheung, Albert C., Liu, Yong, Gan, Min, Wu, Guocheng, Shen, Yanyan

    “…Magnetic resonance (MR) imaging plays an important role in clinical and brain exploration. However, limited by factors such as imaging hardware, scanning time,…”
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  2. 2

    Direct Signal Separation via Extraction of Local Frequencies With Adaptive Time-Varying Parameters by Li, Lin, Chui, Charles K., Jiang, Qingtang

    “…Real-world phenomena that can be formulated as signals are often affected by a number of factors and appear as multi-component modes. To understand and process…”
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  3. 3

    An Effective Video Transformer With Synchronized Spatiotemporal and Spatial Self-Attention for Action Recognition by Alfasly, Saghir, Chui, Charles K., Jiang, Qingtang, Lu, Jian, Xu, Chen

    “…Convolutional neural networks (CNNs) have come to dominate vision-based deep neural network structures in both image and video models over the past decade…”
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  4. 4

    Theory-Inspired Deep Network for Instantaneous-Frequency Extraction and Subsignals Recovery From Discrete Blind-Source Data by Han, Ningning, Mhaskar, H. N., Chui, Charles K.

    “…In the mathematical and engineering literature on signal processing and time-series analysis, there are two opposite points of view concerning the extraction…”
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  5. 5

    Realization of Spatial Sparseness by Deep ReLU Nets With Massive Data by Chui, Charles K., Lin, Shao-Bo, Zhang, Bo, Zhou, Ding-Xuan

    “…The great success of deep learning poses urgent challenges for understanding its working mechanism and rationality. The depth, structure, and massive size of…”
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  6. 6

    On Marcinkiewicz–Zygmund Inequalities and Ap-Weights for L-Shape Arcs by Chui, Charles K., Zhong, Lefan

    Published in The Journal of geometric analysis (2021)
    “…Let Γ be an L -shape arc consisting of 2 line segments that meet at an angle different from π in the complex z -plane C . Application of the exterior conformal…”
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  7. 7

    Deep Nets for Local Manifold Learning by Chui, Charles K., Mhaskar, Hrushikesh N.

    “…The problem of extending a function f defined on a training data C on an unknown manifold 𝕏 to the entire manifold and a tubular neighborhood of this manifold…”
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  8. 8

    Flow-Based Image Abstraction by Kang, H., Seungyong Lee, Chui, C.K.

    “…We present a non-photorealistic rendering technique that automatically delivers a stylized abstraction of a photograph. Our approach is based on shape/color…”
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  9. 9

    Construction of Neural Networks for Realization of Localized Deep Learning by Chui, Charles K., Lin, Shao-Bo, Zhou, Ding-Xuan

    “…The subject of deep learning has recently attracted users of machine learning from various disciplines, including: medical diagnosis and bioinformatics,…”
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  10. 10

    Generative AI Enables Synthesizing Cross-Modality Brain Image via Multi-Level-Latent Representation Learning by You, Senrong, Yuan, Bin, Lyu, Zhihan, Chui, Charles K., Chen, C. L. Philip, Lei, Baiying, Wang, Shuqiang

    “…Multiple brain imaging modalities can provide complementary pathologic information for clinical diagnosis. However, it is huge challenge to acquire enough…”
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  11. 11

    Multirate systems with shortest spline-wavelet filters by Chui, Charles K., de Villiers, Johan, Zhuang, Xiaosheng

    “…Motivated by the need of short FIR filters for perfect-reconstruction multirate systems, the main objective of this paper is to derive the shortest filters for…”
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  12. 12

    Smooth function extension based on high dimensional unstructured data by CHUI, CHARLES K., MHASKAR, H. N.

    Published in Mathematics of computation (01-11-2014)
    “…, but have similar geometric properties, can be arranged to be close neighbors on the manifold. The objective of this paper is to incorporate the consideration…”
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  13. 13

    Deep Net Tree Structure for Balance of Capacity and Approximation Ability by Chui, Charles K., Lin, Shao-Bo, Zhou, Ding-Xuan

    “…Deep learning has been successfully used in various applications including image classification, natural language processing and game theory. The heart of deep…”
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  14. 14

    Tight frame oversampling and its equivalence to shift-invariance of affine frame operators by Chui, Charles K., Sun, Qiyu

    “…Let \Psi=\{\psi_1, \ldots, \psi_L\}\subset L^2:=L^2(-\infty, \infty) generate a tight affine frame with dilation factor M, where 2\le M\in \mathbf{Z}, and…”
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  15. 15

    Tight frames of compactly supported multivariate multi-wavelets by Charina, Maria, Chui, Charles K., He, Wenjie

    “…This paper is devoted to the study and construction of compactly supported tight frames of multivariate multi-wavelets. In particular, a necessary condition…”
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  16. 16

    From extension of Loop's approximation scheme to interpolatory subdivisions by Chui, Charles K., Jiang, Qingtang

    Published in Computer aided geometric design (01-02-2008)
    “…The minimum-supported bivariate C 2 -cubic spline on a 6-directional mesh constructed in our previous work [Chui, C.K., Jiang, Q.T., 2003. Surface subdivision…”
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  17. 17

    PDE models associated with the bilateral filter by Chui, Charles K., Wang, Jianzhong

    Published in Advances in computational mathematics (01-10-2009)
    “…The bilateral filter, introduced in 1998 by Tomasi and Manduchi for feature-preservation image noise-reduction, has recently made significant impacts to other…”
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  18. 18

    Super-resolution wavelets for recovery of arbitrarily close point-masses with arbitrarily small coefficients by Chui, Charles K.

    “…Three families of super-resolution (SR) wavelets Ψv,ng(x), Ψu,n,ms(x) and Ψw,n,mds(x), to be called Gaussian SR (GSR), spline SR (SSR) and dual-spline SR…”
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  19. 19

    Matrix-valued 4-point spline and 3-point non-spline interpolatory curve subdivision schemes by Chui, Charles K., Jiang, Qingtang

    Published in Computer aided geometric design (01-10-2009)
    “…The objective of this paper is to study and construct matrix-valued templates for interpolatory curve subdivision. Since our investigation of this problem was…”
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