Sample class classification method of atom Laplacian regularization-based semi-supervised dictionary learning
A dictionary learning, semi-supervised technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve problems such as less labeled data and the effect of dictionary classification, to ensure simplicity, fast and effective dictionary learning, implementation The effect of constant alternating updates and optimizations
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[0033] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings.
[0034] Such as Figure 1 to Figure 2 As shown in the embodiment of the present invention, the present invention is a semi-supervised dictionary learning method based on atomic Laplacian graph regularization. The specific hardware and programming language of the method of the present invention is not limited, and it is written in any language. All can be done, so other working modes will not be repeated.
[0035] The embodiment of the present invention adopts a computer with Intel Xeon-E5 central processing unit and 16G bytes of memory, and uses Matlab language to compile a working program for semi-supervised dictionary learning based on atomic Laplacian graph regularization, and realizes this Invented method.
[0036] The semi-supervised dictionary learning method ba...
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