obsolete 发表于 2025-3-25 03:40:43

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GNAT 发表于 2025-3-25 10:29:12

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有特色 发表于 2025-3-25 12:43:09

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AGOG 发表于 2025-3-25 19:47:19

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seduce 发表于 2025-3-25 20:12:43

Georgi K. Marinov,William J. Greenleaf in traditional algorithms. Firstly, we use the anisotropic filter to denoise original grayscale images. This method can effectively suppress noise and preserve the edge feature. Secondly, the paper searches optimizing high and low thresholds used in Canny operator utilizing genetic algorithm based

Externalize 发表于 2025-3-26 02:51:43

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Carcinogen 发表于 2025-3-26 08:08:28

https://doi.org/10.1007/978-1-0716-2899-7jugacy, we firstly define an .-norm and induce a family of penalty functions for structured sparsity. Then we build and discuss some important properties of these functions. By introducing the multiplicative auxiliary variable in HQ, we further reformulate the structured sparsity problem as an augme

Inflated 发表于 2025-3-26 11:37:01

https://doi.org/10.1007/978-3-319-52183-1ewpoints, lightings or complex backgrounds. In order to detect and localize the human hands in static images against complex backgrounds, a hand detection method based on a mixture of multi-scale deformable part models is proposed in this paper, which is trained discriminatively using latent SVM and

勉励 发表于 2025-3-26 16:40:21

A Condensed History of Chromatin Research, the Gram matrix. The new method can reduce the mutual coherence between the measurement matrix and the sparse transform matrix. Numerical experiments verify the success of the optimized method. Compared with the original Gaussian random matrix and other optimized measurement matrices, the performan

SPER 发表于 2025-3-26 18:26:04

Results and Problems in Cell Differentiationrigid point set. Firstly, a new cost function was constructed to evaluate the summation of squared distance between the two point sets, in which rigid transformation, non-rigid elastic deformation and complex deformation were all included for consideration. Secondly, the proposed cost was linearized
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查看完整版本: Titlebook: Advances in Image and Graphics Technologies; 11th Chinese Confere Tieniu Tan,Guoping Wang,Sheng Li Conference proceedings 2016 Springer Sci