Importance in the occurrence rate of shortest buccal bone marrow distance (&lt;1 mm) for sagittal split ramus osteotomy

Chen, Chun‐Ming; Liang, Shih-Wei; Chou, Szu-Ting; Hwang, Dae-Seok; Kim, Uk-Kyu; Tseng, Yu-Chuan

doi:10.1016/j.jfma.2020.07.030

Cited by 1 publication

(1 citation statement)

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“…Here, β is the sensitivity coefficient to adjust the main color difference of the image, and the general value is set at 0.5. By calculating the shortest Euclidean distance between the vertex Vu ′ and the foreground seed and background seed in the image [ 21 , 22 ], the degree of overlap of the main color distribution in the image can be obtained. The calculation method of Euclidean distance is shown in formulas ( 8 ) and ( 9 ):

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Section: Realize the Style Transfer Of Art Workmentioning

confidence: 99%

Style Transfer of Chinese Art Works Based on Dual Channel Deep Learning Model

Tang

2022

Computational Intelligence and Neuroscience

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Aiming at the problems of style loss and lack of content in the style transfer of Chinese art works, this paper puts forward the style transfer technology of Chinese art works based on the dual channel deep learning model. On the basis of clarifying the technical principle of style transfer of art works, the image of art works is controlled and transformed based on the u-net network. The incomplete information in the restored image is filled, and the multiscale classification feature is used to calculate the color feature data items in the image. The sensitivity coefficient of color difference is calculated by using constraints, and the overlapping color discrimination and image segmentation of art images are realized. Poisson image editing is used to constrain the image spatial gradient to realize the style migration of art works. The experimental results show that this method can effectively avoid the problems of content error, distortion, and distortion in the process of art style migration, and has a better style migration effect.

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Section: Realize the Style Transfer Of Art Workmentioning

confidence: 99%