Titlebook: Computer Vision and Graphics; International Confer Leszek J. Chmielewski,Amitava Datta,Konrad Wojciec Conference proceedings 2016 Springer

Colossal

书目名称Computer Vision and Graphics影响因子(影响力)




书目名称Computer Vision and Graphics影响因子(影响力)学科排名




书目名称Computer Vision and Graphics网络公开度




书目名称Computer Vision and Graphics网络公开度学科排名




书目名称Computer Vision and Graphics被引频次




书目名称Computer Vision and Graphics被引频次学科排名




书目名称Computer Vision and Graphics年度引用




书目名称Computer Vision and Graphics年度引用学科排名




书目名称Computer Vision and Graphics读者反馈




书目名称Computer Vision and Graphics读者反馈学科排名

掺假

https://doi.org/10.1007/978-1-4842-7310-4e in the detection between the maps created by humans and computed by SSIM. The results of the cross-validation performed on a large collection of examples revealed that AUC (area under curve) in the receiver-operator analysis can be improved from 0.92 for default SSIM parameters to 0.97 for optimis

Anal-Canal

圣人

Single Image Haze Removal Using Single Pixel Approach Based on Dark Channel Prior with Fast FilterinSM is the main reason for the slowness of DCP. The proposed algorithm is faster than existing methods, but achieves similar dehazing. This new method is useful for applications that require fast dehazing.

刚毅

Encumber

RMagick: ImageMagick Programming with Ruby,to reduce the database size and made the subjective experiments less expensive and therefore more usable. To achieve it we employ a clustering technique and human visual system based objective metrics.

Encumber

DEMUR

The Definitive Guide to JasperReportsis paper is to present a comparative analysis of several methods (finite differences, interpolation, operators and regularization), that have been developed for numerical differentiation. Numerical results are presented for artificial and real data sets.

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Perceptual Experiments Optimisation by Initial Database Reductionto reduce the database size and made the subjective experiments less expensive and therefore more usable. To achieve it we employ a clustering technique and human visual system based objective metrics.

BLANK

Anisotropic Diffusion for Smoothing: A Comparative Study of this paper is to present a comparative study of three methods that have been used for smoothing using anisotropic diffusion techniques. These methods have been compared using the root mean square error (RMSE) and the Nash-Sutcliffe error. Numerical results are presented for both artificial data and real data.