1,031 research outputs found
Syntheisis, Redox Properties and Reactivities of Ruthenium(II) Complexes of 1,1'-Biisquinoline(BIQN) and X-ray Crystal Structure of[RuⅡ(terpy)(BIQN)(Cl)]ClO4 (terpy=2,2':6', 2"-Terpyridine)
No full textCong liang zi xin xi xue de jiao du tan tao yi xie liang zi xiang bian zhong de ji ben wen ti
No full textYu, Wing Chi = 從量子信息學的角度探討一些量子相變中的基本問題 / 余詠芝.Thesis Ph.D. Chinese University of Hong Kong 2014.Includes bibliographical references (leaves 131-139).Abstracts also in Chinese.Title from PDF title page (viewed on 03, November, 2016).Yu, Wing Chi = Cong liang zi xin xi xue de jiao du tan tao yi xie liang zi xiang bian zhong de ji ben wen ti / Yu Yongzhi
Synthesis, redox properties and reactivities of ruthenium(II) complexes of 1,1′-biisoquinoline (BIQN) and X-ray crystal structure of [RuII(terpy)(BIQN)(Cl)]ClO4 (terpy = 2,2′:6′, 2?-terpyridine)
No full textLocal Color Transfer via Probabilistic Segmentation by Expectation-Maximization
No full textWe address the problem of regional color transfer between two natural images by probabilistic segmentation. We use a new expectation-maximization (EM) scheme to impose both spatial and color smoothness to infer natural connectivity among pixels. Unlike previous work, our method takes local color information into consideration, and segment image with soft region boundaries for seamless color transfer and compositing. Our modified EM method has two advantages in color manipulation: first, subject to different levels of color smoothness in image space, our algorithm produces an optimal number of regions upon convergence, where the color statistics in each region can be adequately characterized by a component of a Gaussian mixture model (GMM). Second, we allow a pixel to fall in several regions according to our estimated probability distribution in the EM step, resulting in a transparency-like ratio for compositing different regions seamlessly. Hence, natural color transition across regions can be achieved, where the necessary intra-region and inter-region smoothness are enforced without losing original details. We demonstrate results on a variety of applications including image deblurring, enhanced color transfer, and colorizing gray scale images. Comparisons with previous methods are also presented
Perceptually-inspired and edge-directed color image super-resolution
No full textInspired by multi-scale tensor voting, a computational framework for perceptual grouping and segmentation, we propose an edge-directed technique for color image superresolution given a single low-resolution color image. Our multi-scale technique combines the advantages of edgedirected, reconstruction-based and learning-based methods, and is unique in two ways. First, we consider simultaneously all the three color channels in our multi-scale tensor voting framework to produce a multi-scale edge representation to guide the process of high-resolution color image reconstruction, which is subject to the back projection constraint. Fine details are inferred without noticeable blurry or ringing artifacts. Second, the inference of highresolution curves is achieved by multi-scale tensor voting, using the dense voting field as an edge-preserving smoothness prior which is derived geometrically without any timeconsuming learning procedure. Qualitative and quantitative results indicate that our method produces convincing results in complex test cases typically used by state-of-theart image super-resolution techniques
Simultaneous Image Denoising and Compression by Multiscale 2D Tensor Voting
No full textIn this paper we propose a method that simultaneously performs image denoising and compression by using multiscale tensor voting. Given a real color image, the pixels are first converted into a set of tokens to be grouped by tensor voting, where optimal scales are automatically selected among others for perceptual grouping and faithful reconstruction. Tensor voting at multiple scales are performed at all input tokens to infer the feature grouping attributes such as region-ness, curve-ness, and junctionness with their optimal scales. We perform experiments on complex real images to demonstrate the robustness of our metho
Chiral ruthenium(IV)-oxo complexes. Structure, reactivities of [Ru(terpy)(N∩N)O]2+ (N∩N = N,N,N′,N′-tetramethyl-1,2-diaminocyclohexane) and [Ru(Me3tacn)(cbpy)O]2+ (cbpy = (?)-3,3′-[(4S-trans)-1,3-dioxolane-4,5-dimethyl]-2,2′-bipyridine)
No full textDuo ti xi tong zhong de liang zi xiang bian dong li xue
No full textYu, Wing Chi = 多體系統中的量子相變動力學 / 余詠芝.Thesis (M.Phil.)--Chinese University of Hong Kong, 2011.Includes bibliographical references (leaves 94-99).Abstracts in English and Chinese.Yu, Wing Chi = Duo ti xi tong zhong de liang zi xiang bian dong li xue / Yu Yongzhi.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Quantum phase transitions --- p.1Chapter 1.2 --- Schemes detecting QPTs --- p.3Chapter 1.2.1 --- Traditional schemes --- p.3Chapter 1.2.2 --- Quantum Entanglement --- p.4Chapter 1.2.3 --- Quantum fidelity --- p.4Chapter 1.2.4 --- Loschmidt echoes --- p.5Chapter 1.2.5 --- Quench dynamics --- p.6Chapter 1.3 --- Motivation --- p.7Chapter 2 --- Theoretical framework --- p.9Chapter 2.1 --- Quantum Zeno effect --- p.9Chapter 2.2 --- Mathematical formulation --- p.11Chapter 2.3 --- Remarks --- p.14Chapter 3 --- Analysis on the One-dimensional Transverse-field Ising model --- p.17Chapter 3.1 --- The model --- p.17Chapter 3.2 --- Diagonalization of the Hamiltonian --- p.20Chapter 3.2.1 --- Jordan-Wigner transformation --- p.20Chapter 3.2.2 --- Fourier Transformation --- p.24Chapter 3.2.3 --- Bogoliubov transformation --- p.26Chapter 3.3 --- Quantum Zeno dynamics in the model --- p.28Chapter 3.3.1 --- Analytical calculation of the Zeno susceptibility --- p.28Chapter 3.3.2 --- Validity of the analytical result --- p.31Chapter 3.3.3 --- Scaling behavior of the Zeno susceptibility --- p.33Chapter 3.3.4 --- Zeno susceptibility around the critical point --- p.35Chapter 3.4 --- Conclusion and experimental outlook --- p.38Chapter 4 --- Analysis on the Lipkin-Meshkov-Glick Model --- p.40Chapter 4.1 --- The model --- p.41Chapter 4.2 --- Diagonalization of the Hamiltonian --- p.46Chapter 4.2.1 --- Holstein-Primakoff transformation --- p.46Chapter 4.2.2 --- Bogoliubov transformation --- p.49Chapter 4.3 --- Quantum Zeno dynamics in the model --- p.51Chapter 4.3.1 --- Analytical form of the Zeno susceptibility and its scaling behavior --- p.51Chapter 4.3.2 --- Validity of the analytical result --- p.54Chapter 4.3.3 --- Numerical analysis of the Zeno susceptibility --- p.55Chapter 4.4 --- Conclusion --- p.60Chapter 5 --- Analysis on the Kitaev model on a honeycomb lattice --- p.61Chapter 5.1 --- The model --- p.61Chapter 5.2 --- Diagonalization of the Hamiltonian --- p.63Chapter 5.2.1 --- Jordan-Wigner transformation for two-dimensional systems --- p.64Chapter 5.2.2 --- Majorana fermion representation --- p.68Chapter 5.2.3 --- Fermions on the 之-bonds --- p.71Chapter 5.2.4 --- Bogoliubov transformation --- p.73Chapter 5.3 --- Energy spectrum --- p.75Chapter 5.4 --- Quantum Zeno dynamics in the model --- p.77Chapter 5.4.1 --- Coupling along the Jx = Jy line --- p.77Chapter 5.4.2 --- Coupling along the line with constant Jz --- p.83Chapter 5.5 --- Conclusion --- p.90Chapter 6 --- Conclusion and outlook --- p.91Bibliography --- p.94Chapter A --- Perturbative form of the Loschimdt Echo --- p.100Chapter B --- Hellmann-Feynman theorem --- p.107Chapter C --- Commutation relations in the Jordan-Wigner transformation --- p.10
Soft color segmentation and its applications
No full textWe propose an automatic approach to soft color segmentation, which produces soft color segments with appropriate amount of overlapping and transparency essential to synthesizing natural images for a wide range of image-based applications. While many state-of-the-art and complex techniques are excellent at partitioning an input image to facilitate deriving a semantic description of the scene, to achieve seamless image synthesis, we advocate to a segmentation approach designed to maintain spatial and color coherence among soft segments while preserving discontinuities, by assigning to each pixel a set of soft labels corresponding to their respective color distributions. We optimize a global objective function which simultaneously exploits the reliability given by global color statistics and flexibility of local image compositing, leading to an image model where the global color statistics of an image is represented by a Gaussian Mixture Model (GMM), while the color of a pixel is explained by a local color mixture model where the weights are defined by the soft labels to the elements of the converged GMM. Transparency is naturally introduced in our probabilistic framework which infers an optimal mixture of colors at an image pixel.To adequately consider global and local information in the same framework, an alternating optimization scheme is proposed to iteratively solve for the global and local model parameters. Our method is fully automatic, and is shown to converge to a good optimal solution. We perform extensive evaluation and comparison, and demonstrate that our method achieves good image synthesis results for image-based applications such as image matting, color transfer, image deblurring, and image colorization.</p
Alkyne Oxidations by cis-Dioxoruthenium(VI) Complexes. A Formal [3 + 2] Cycloaddition Reaction of Alkynes with cis-[(Cn*)(CF3CO2)RuVIO2]ClO4 (Cn* = 1,4,7-Trimethyl-1,4,7-triazacyclononane)
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