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Effects of mesh style and grid convergence on numerical simulation accuracy of centrifugal pump 被引量:2
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作者 刘厚林 刘明明 +1 位作者 白羽 董亮 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第1期368-376,共9页
In order to evaluate the effects of mesh generation techniques and grid convergence on pump performance in centrifugal pump model, three widely used mesh styles including structured hexahedral, unstructured tetrahedra... In order to evaluate the effects of mesh generation techniques and grid convergence on pump performance in centrifugal pump model, three widely used mesh styles including structured hexahedral, unstructured tetrahedral and hybrid prismatic/tetrahedral meshes were generated for a centrifugal pump model. And quantitative grid convergence was assessed based on a grid convergence index(GCI), which accounts for the degree of grid refinement. The structured, unstructured or hybrid meshes are found to have certain difference for velocity distributions in impeller with the change of grid cell number. And the simulation results have errors to different degrees compared with experimental data. The GCI-value for structured meshes calculated is lower than that for the unstructured and hybrid meshes. Meanwhile, the structured meshes are observed to get more vortexes in impeller passage.Nevertheless, the hybrid meshes are found to have larger low-velocity area at outlet and more secondary vortexes at a specified location than structured meshes and unstructured meshes. 展开更多
关键词 mesh style grid convergence index(GCI) numerical simulation particle image velocimetry(PIV) centrifugal pump
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Implementation of Art Pictures Style Conversion with GAN
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作者 Xinlong Wu Desheng Zheng +3 位作者 Kexin Zhang Yanling Lai Zhifeng Liu Zhihong Zhang 《Journal of Quantum Computing》 2021年第4期127-136,共10页
Image conversion refers to converting an image from one style to another and ensuring that the content of the image remains unchanged.Using Generative Adversarial Networks(GAN)for image conversion can achieve good res... Image conversion refers to converting an image from one style to another and ensuring that the content of the image remains unchanged.Using Generative Adversarial Networks(GAN)for image conversion can achieve good results.However,if there are enough samples,any image in the target domain can be mapped to the same set of inputs.On this basis,the Cycle Consistency Generative Adversarial Network(CycleGAN)was developed.This article verifies and discusses the advantages and disadvantages of the CycleGAN model in image style conversion.CycleGAN uses two generator networks and two discriminator networks.The purpose is to learn the mapping relationship and inverse mapping relationship between the source domain and the target domain.It can reduce the mapping and improve the quality of the generated image.Through the idea of loop,the loss of information in image style conversion is reduced.When evaluating the results of the experiment,the degree of retention of the input image content will be judged.Through the experimental results,CycleGAN can understand the artist’s overall artistic style and successfully convert real landscape paintings.The advantage is that most of the content of the original picture can be retained,and only the texture line of the picture is changed to a level similar to the artist’s style. 展开更多
关键词 Generative adversary network deep learning image style conversion convolutional neural network adversary learning
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Read The film "Three idiots" and reflect the current situation
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作者 Li Mengjiao Lin Yan 《International Journal of Technology Management》 2014年第10期48-50,共3页
The Three Idiots, has a Strong appreciation ,with excellent script, creative actor, sophisticated production, fine plot, the endless stream of jokes. It uses a variety of narrative technique and also gives insight to ... The Three Idiots, has a Strong appreciation ,with excellent script, creative actor, sophisticated production, fine plot, the endless stream of jokes. It uses a variety of narrative technique and also gives insight to audiences on the various time lines clearly, Dance also added a beautiful landscape to the film. We can learn from the achievements on Artistic and box office and it reflects the present situation of Indian society. 展开更多
关键词 image style Character Analysis Dance teaser Comedy elements REALISTIC
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Reference-guided structure-aware deep sketch colorization for cartoons 被引量:2
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作者 Xueting Liu Wenliang Wu +2 位作者 Chengze Li Yifan Li Huisi Wu 《Computational Visual Media》 SCIE EI CSCD 2022年第1期135-148,共14页
Digital cartoon production requires extensive manual labor to colorize sketches with visually pleasant color composition and color shading.During colorization,the artist usually takes an existing cartoon image as colo... Digital cartoon production requires extensive manual labor to colorize sketches with visually pleasant color composition and color shading.During colorization,the artist usually takes an existing cartoon image as color guidance,particularly when colorizing related characters or an animation sequence.Reference-guided colorization is more intuitive than colorization with other hints,such as color points or scribbles,or text-based hints.Unfortunately,reference-guided colorization is challenging since the style of the colorized image should match the style of the reference image in terms of both global color composition and local color shading.In this paper,we propose a novel learning-based framework which colorizes a sketch based on a color style feature extracted from a reference color image.Our framework contains a color style extractor to extract the color feature from a color image,a colorization network to generate multi-scale output images by combining a sketch and a color feature,and a multi-scale discriminator to improve the reality of the output image.Extensive qualitative and quantitative evaluations show that our method outperforms existing methods,providing both superior visual quality and style reference consistency in the task of reference-based colorization. 展开更多
关键词 sketch colorization image style editing deep feature understanding reference-based image colorization
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