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

Colossal

書目名稱Computer Vision and Graphics影響因子(影響力)




書目名稱Computer Vision and Graphics影響因子(影響力)學科排名




書目名稱Computer Vision and Graphics網(wǎng)絡(luò)公開度




書目名稱Computer Vision and Graphics網(wǎng)絡(luò)公開度學科排名




書目名稱Computer Vision and Graphics被引頻次




書目名稱Computer Vision and Graphics被引頻次學科排名




書目名稱Computer Vision and Graphics年度引用




書目名稱Computer Vision and Graphics年度引用學科排名




書目名稱Computer Vision and Graphics讀者反饋




書目名稱Computer Vision and Graphics讀者反饋學科排名

摻假

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.

剛毅

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.