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Criminal law imputation path for biometric information

Yifang Wang

Yifang Wang

Law School, Ocean University of ChinaChina
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Wang, Yifang
  
23. Dez. 2022
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Online veröffentlicht: 23. Dez. 2022
Seitenbereich: 2705 - 2716
Eingereicht: 08. Juli 2022
Akzeptiert: 07. Aug. 2022
DOI: https://doi.org/10.2478/amns.2021.2.00280
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© 2023 Yifang Wang, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Minimum uncertainty neural network structure. [A] Layer: the sample input layer; A is the observed value, and Xii is the observed value of the attribute xi. [B] Layer: weight selection layer, when xii′ ∈ A, Oii′ = 1; otherwise, Oii′ = 0. [C] Layer: weighted calculation layer; there is Eq. (8) to get sj. [D] Layer: Uncertainty output layer, and the πj output is obtained by using Eqs (11) and (12)
Minimum uncertainty neural network structure. [A] Layer: the sample input layer; A is the observed value, and Xii is the observed value of the attribute xi. [B] Layer: weight selection layer, when xii′ ∈ A, Oii′ = 1; otherwise, Oii′ = 0. [C] Layer: weighted calculation layer; there is Eq. (8) to get sj. [D] Layer: Uncertainty output layer, and the πj output is obtained by using Eqs (11) and (12)

Fig. 2

Training curve of recognition rate
Training curve of recognition rate
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