Selection of Informative Template in Hierarchical Sparse Method

Alsaidi, Ramadhan Abdo Musleh; Li, Hon G; Li, Hongf Eng; Khaji, Rokan

doi:10.14445/22315373/ijmtt-v53p559

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2020

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“…The importance of this connection rely on the fact where function is capable of mapping a set of feature paths from the lower patches to a solitary feature path at the upper patches. Reader is recommended to consult [24,25,28] for further detail treatment.…”

Section: The Proposed Methodsmentioning

confidence: 99%

“…The aim of this research work is to solve the above issues and address it by improving the ability to distinguish in picking effective models based on entropy measures. Where Shannon entropy [28] plays a considerable role by computing several templates. Therefore leading to provide an efficient way to evaluate the insight properties of the neural response.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Using Derived kernel as a new Method for Recognition a Similarity Learning.

Alsaidi,

Alanzi,

Alenazi

et al. 2020

IJEAT

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A new technique for feature withdrawal by neural response is going to be familiarized in this research work by merging an entropy measure with Squared Pearson correlation Coefficient (SPCC) method. The process of choosing effective models on the basis of entropy measures was proposed further to enhance the ability to select templates. For more accurate similarity measure we used the statistical significant relationship between functions. The research illustrate that the proposed method is proficiently compared with the state-of-the-art methods.

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Section: The Proposed Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%