Parameter Definition for Multilayer Perceptron Intended for Speaker Identification

Tereikovskyi, Ihor; Subach, Ihor; Tereikovskyi, Oleh; Tereikovska, Liudmyla; Tolіupa, Serhii; Nakonechnyi, Volodymyr

doi:10.1109/atit49449.2019.9030504

Cited by 7 publications

(6 citation statements)

References 17 publications

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“…Where w represents the weights vector, x represents the inputs vector, b represents the bias, and φ represents the activation function [18].…”

Section: The Proposed Pdmlp Methodsmentioning

confidence: 99%

PDMLP: Phishing Detection Using Multilayer Perceptron

Al-Ahmadi

2020

SSRN Journal

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A phishing website is a significant problem on the internet. It's one of the Cyber-attack types where attackers try to obtain sensitive information such as username and password or credit card information. The recent growth in deploying a Detection phishing URL system on many websites has resulted in a massive amount of available data to predict phishing websites. In this paper, we purpose a new method to develop a phishing detection system called phishing detection based on a multilayer perceptron (PDMLP), which used on two types of datasets. The performance of these mechanisms evaluated in terms of Accuracy, Precision, Recall, and F-measure. Results showed that PDMLP provides better performance in comparison to KNN, SVM, C4.5 Decision Tree, RF, and RoF to classifiers.

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“…Where w represents the weights vector, x represents the inputs vector, b represents the bias, and φ represents the activation function [18].…”

Section: The Proposed Pdmlp Methodsmentioning

confidence: 99%

PDMLP: Phishing Detection Using Multilayer Perceptron

Al-Ahmadi

2020

SSRN Journal

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“…As shown by the results of the analysis of scientific and practical work [5,7,8], one of the main directions of development of neural network means of recognizing a person's face and emotions on the face and iris is to increase the adaptability of these tools to expected operating conditions. However, in [6,[9][10][11][12] it was noted that typical interferences that significantly complicate the recognition process are mainly caused by:  The presence of objects that cover part of the image.…”

Section: Related Workmentioning

confidence: 99%

“…5. Example of filtering a face image using MATLAB Therefore, the filtering procedure it is used the results of [20], which presents an approach to selecting the most efficient basic wavelet, which meets the need to achieve sufficient accuracy of spectral analysis with minimal computational costs and is described by expressions (7,8). To determine these expressions formed, given in table.…”

Section: Development Of the Mathematical Apparatusmentioning

confidence: 99%

“… Expertly determine the value of criterion e12.  Using expression (8) to calculate the efficiency of each type of basic wavelet.  Using expression (7) to determine the most effective type of basic wavelet.…”

Section: Criterion Type Of Basic Wavelet Haar Mhat Fhat Wavementioning

confidence: 99%

“…Expertly obtained values of the criterion e 12 are given in table 4. The calculation of the integrated efficiency index of each of the tested types of basic wavelets is implemented by substituting the data of table 2-4 in expression (8). The results obtained are given in table 5.…”

Section: Criterion Type Of Basic Wavelet Haar Mhat Fhat Wavementioning

confidence: 99%

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Procedure for Processing Biometric Parameters Based on Wavelet Transformations

Hu¹,

Tereikovskyi²,

Chernyshеv³

et al. 2021

IJMECS

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The problem of the article is related to the improvement of means of covert monitoring of the face and emotions of operators of information and control systems on the basis of biometric parameters that correlate with twodimensional monochrome and color images. The difficulty in developing such tools has been shown to be largely due to the cleaning of images associated with biometric parameters from typical non-stationary interference caused by uneven lighting and foreign objects that interfere with video recording. The possibility of overcoming these difficulties by using wavelet transform technology, which is used to filter images by combining several identical, but differently noisy monochrome and color images, is substantiated. It is determined that the development of technology for the use of wavelet transforms is primarily associated with the choice of the type of basic wavelet, the parameters of which must be adapted to the conditions of use in a particular system of covert monitoring of personality and emotions. An approach to choosing the type of basic wavelet that is most effective in filtering images from non-stationary interference is proposed. The approach is based on a number of the proposed provisions and efficiency criteria that allow to ensure when choosing the type of basic wavelet taking into account the significant requirements of the task. A filtering procedure has been developed, which, due to the application of the specified video image filtering technology and the proposed approach to the choice of the basic wavelet type, allows to effectively clean the images associated with biometric parameters from typical non-stationary interference. The conducted experimental studies have shown the feasibility of using the developed procedure for filtering images of the face and iris of operators of information and control systems.

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