制定法律 发表于 2025-3-25 05:41:01

Kernel Learning Foundation,el methods are algorithms that, by replacing the inner product with an appropriate positive definite function, implicitly perform a nonlinear mapping of the input data to a high-dimensional feature space.

我还要背着他 发表于 2025-3-25 09:17:26

Kernel Discriminant Analysis Based Face Recognition,essful in a lot of real-world applications. LDA works well in some cases, but it fails to capture a nonlinear relationship with a linear mapping. In order to overcome this weakness of LDA, the kernel trick is used to represent the complicated nonlinear relationships of input data to develop kernel discriminant analysis (KDA) algorithm.

d-limonene 发表于 2025-3-25 15:21:57

Kernel Manifold Learning-Based Face Recognition,n aims to develop a meaningful low-dimensional subspace in a high-dimensional input space such as PCA and LDA. LDA is to find the optimal projection matrix with Fisher criterion through considering the class labels, and PCA seeks to minimize the mean square error criterion.

集合 发表于 2025-3-25 17:37:44

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ineptitude 发表于 2025-3-25 23:08:20

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说明 发表于 2025-3-26 03:07:20

978-1-4939-5212-0Springer Science+Business Media New York 2014

thwart 发表于 2025-3-26 05:29:52

Jun-Bao Li,Shu-Chuan Chu,Jeng-Shyang PanDiscusses the system framework of kernel based face recognition.Introduces a new method of machine learning as it relates to face recognition.Presents algorithms for pattern recognition and machine le

落叶剂 发表于 2025-3-26 09:44:52

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慷慨不好 发表于 2025-3-26 12:37:04

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Lipohypertrophy 发表于 2025-3-26 17:02:20

Kernel-Optimization-Based Face Recognition,Feature extraction is an important step and essential process in many data analysis areas, such as face recognition, handwriting recognition, human facial expression analysis, speech recognition.
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查看完整版本: Titlebook: Kernel Learning Algorithms for Face Recognition; Jun-Bao Li,Shu-Chuan Chu,Jeng-Shyang Pan Book 2014 Springer Science+Business Media New Yo