The development of algorithms to solve Many-objective optimization problems(MaOPs) has attracted significant research interest in recent *** various types of Pareto front(PF) is a daunting challenge for evolutionary a...
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The development of algorithms to solve Many-objective optimization problems(MaOPs) has attracted significant research interest in recent *** various types of Pareto front(PF) is a daunting challenge for evolutionary algorithm. A Research mode based evolutionary algorithm(RMEA) is proposed for many-objective optimization. The archive in the RMEA is used to store non-dominated solutions that can reflect the shape of the PF to guide the reference vector *** concerning the population is collected, once the number of non-dominated solutions reaches its limit after many generations without exceeding a given threshold, RMEA introduces a research mode that generates more reference vectors to search through the solutions. The proposed algorithm showed competitive performance with four state-of-the-art evolutionary algorithms in a large number of experiments.
Aiming to solve the poor performance of low illumination enhancement algorithms on uneven illumination images,a low-light image enhancement(LIME)algorithm based on a residual network was *** algorithm constructs a dee...
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Aiming to solve the poor performance of low illumination enhancement algorithms on uneven illumination images,a low-light image enhancement(LIME)algorithm based on a residual network was *** algorithm constructs a deep network that uses residual modules to extract image feature information and semantic modules to extract image semantic information from different ***,a composite loss function was also designed for the process of low illumination image enhancement,which dynamically evaluated the loss of an enhanced image from three factors of color,structure,and *** ensures that the model can correctly enhance the image features according to the image semantics,so that the enhancement results are more in line with the human visual *** results show that compared with the state-of-the-art algorithms,the semantic-driven residual low-light network(SRLLN)can effectively improve the quality of low illumination images,and achieve better subjective and objective evaluation indexes on different types of images.
Two-dimensional (2-D) array sets with good 2-D correlation properties have received considerable attention in wireless communication systems. This paper focuses on 2-D Z-complementary array code sets (ZCACSs), which h...
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For learning-based super-resolution reconstruction, the selection and training of dictionary play an important role in improving image reconstruction quality. A super-resolution algorithm based on two dictionary-pairs...
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Voice conversion (VC) based on Gaussian mixture model (GMM) is the most classic and common method which converts the source spectrum to target spectrum. However this method is prone to over-fitting because of its ...
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Voice conversion (VC) based on Gaussian mixture model (GMM) is the most classic and common method which converts the source spectrum to target spectrum. However this method is prone to over-fitting because of its frame-by-frame conversion. The VC with non-negative matrix factorization (NMF) is presented in this paper, which can keep spectrum from over-fitting by adjusting the size of basis vector (dictionary). In order to realize the non-linear mapping better, kernel NMF (KNMF) is adopted to achieve spectrum mapping. In addition, to increase the accuracy of conversion, KNMF combined with GMM (GKNMF) is also introduced into VC. In the end, KNMF, GKNMF, GMM, principal component regression (PCR), PCR combined with GMM (GPCR), partial least square regression (PLSR), NMF correlation-based frequency warping (NMF-CFW) and deep neural network (DNN) methods are compared with each other. The proposed GKNMF gets better performance in both objective evaluation and subjective evaluation.
To solve the super-resolution reconstruction problem for single-frame image, an algorithm based on sparse representation and nonlocal regularization is proposed. By training the joint dictionaries, this algorithm look...
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Conventional single-chip digital cameras use color filter arrays(CFA) to sample different spectral components. image demosaicing is a problem of interpolating these data to complete red, green, and blue values for eac...
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ISBN:
(纸本)9781467321969
Conventional single-chip digital cameras use color filter arrays(CFA) to sample different spectral components. image demosaicing is a problem of interpolating these data to complete red, green, and blue values for each image pixel, to produce an RGB image. Many color demosaicing(CDM) methods assume that the high local spatial redundancy exists among the color samples. Such an assumption, however, may be fail for images with high color saturation and sharp color transitions. This paper presents an adaptive demosaicing algorithm by exploiting both the non-local similarity and the local correlation(NLS-LC) in the color filter array image. First, the most flattest nonlocal image patches are searched in the searching window centered on the estimated pixel. Second, the patch, which is the most similar to the current patch, is selected among the most smoothest nonlocal patches. Third, according to the similar degree and the local correlation degree, the obtained nonlocal image patch and the current patch are adaptively chosen to estimate the missing color samples. Experimental results indicate that the proposed method exhibits superior performance over many state-of-the-art color interpolation methods.
The study utilized a human-centered perspective to research the financial markets, focusing on identifying variations in eye movement patterns between professional and non-professional traders as they analyze a series...
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Influence of intramolecular π-π interaction on the luminescent properties of thermally activated delayed fluorescence(TADF) molecule(3, 5-bis(3,6-di-tert-butyl-9 H-carbazol-9-yl)-phenyl)(pyridin-4-yl) methan...
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Influence of intramolecular π-π interaction on the luminescent properties of thermally activated delayed fluorescence(TADF) molecule(3, 5-bis(3,6-di-tert-butyl-9 H-carbazol-9-yl)-phenyl)(pyridin-4-yl) methanone(DTCBPY) is theoretically studied by using the density functional theory(DFT) and time-dependent density functional theory(TD-DFT).Four conformations(named as A, B, C, and D) of the DTCBPY can be found by relax scanning, and the configuration C corresponds to the luminescent molecule detected experimentally. Besides, we calculate the proportion of each conformation by Boltzmann distribution, high configuration ratios(44% and 52%) can be found for C and D. Moreover, C and D are found to exist with an intramolecular π-π interaction between one donor and the acceptor; the intramolecular interaction brings a smaller Huang-Rhys factor and reduced reorganization energy. Our work presents a rational explanation for the experimental results and demonstrates the importance of the intramolecular π-π interaction to the photophysical properties of TADF molecules.
The excited state intramolecular proton transfer of four derivatives(FM, BFM, BFBC, CCM) of 3-hydroxychromone is *** geometries of different substituents are optimized to study the substituent effects on proton *** me...
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The excited state intramolecular proton transfer of four derivatives(FM, BFM, BFBC, CCM) of 3-hydroxychromone is *** geometries of different substituents are optimized to study the substituent effects on proton *** mechanism of hydrogen bond enhancement is qualitatively elucidated by comparing the infrared spectra, the reduced density gradient, and the frontier molecular *** calculated electronic spectra are consistent with the experimental *** quantify the proton transfer, the potential energy curves(PECs) of the four derivatives in S0 and S1 states are *** is concluded that the ability of proton transfer follows the order: FM > BFM > BFBC > CCM.
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