Determination of Signs of Information and Psychological Influence in the Tone of Sound Sequences

Юдін, О. К.; Tolіupa, Serhii; Корченко, Олександр Григорович; Tereikovska, Liudmyla; Tereikovskyi, Ihor; Tereikovskyi, Oleh

doi:10.1109/atit50783.2020.9349302

Cited by 4 publications

(5 citation statements)

References 16 publications

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“…The database used to form the training, validation, and the test sample is specified. According to the recommendations [21,24] The graphs of the accuracy indicators of the segmentation of nerve plexuses built on the basis of the results of experiments conducted using the U-Net, PSPNet and YOLOv4 neural network models are shown in fig. 3-5.…”

Section: Development and Research Of A Neural Network Modelmentioning

confidence: 99%

A Neural Network Model for Object Mask Detection in Medical Images

Tereikovskyi,

Korchenko,

Bushuyev

et al. 2022

International Journal of Electronics and Telecommunications

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In modern conditions in the field of medicine, raster image analysis systems are becoming more widespread, which allow automating the process of establishing a diagnosis based on the results of instrumental monitoring of a patient. One of the most important stages of such an analysis is the detection of the mask of the object to be recognized on the image. It is shown that under the conditions of a multivariate and multifactorial task of analyzing medical images, the most promising are neural network tools for extracting masks. It has also been determined that the known detection tools are highly specialized and not sufficiently adapted to the variability of the conditions of use, which necessitates the construction of an effective neural network model adapted to the definition of a mask on medical images. An approach is proposed to determine the most effective type of neural network model, which provides for expert evaluation of the effectiveness of acceptable types of models and conducting computer experiments to make a final decision. It is shown that to evaluate the effectiveness of a neural network model, it is possible to use the Intersection over Union and Dice Loss metrics. The proposed solutions were verified by isolating the brachial plexus of nerve fibers on grayscale images presented in the public Ultrasound Nerve Segmentation database. The expediency of using neural network models U-Net, YOLOv4 and PSPNet was determined by expert evaluation, and with the help of computer experiments, it was proved that U-Net is the most effective in terms of Intersection over Union and Dice Loss, which provides a detection accuracy of about 0.89. Also, the analysis of the results of the experiments showed the need to improve the mathematical apparatus, which is used to calculate the mask detection indicators.

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Section: Development and Research Of A Neural Network Modelmentioning

confidence: 99%

A Neural Network Model for Object Mask Detection in Medical Images

Tereikovskyi,

Korchenko,

Bushuyev

et al. 2022

International Journal of Electronics and Telecommunications

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“…Classical frequency filtering methods are based on spectral analysis of images using a discrete Fourier transform. The disadvantages of such methods are caused by the limitations of the Fourier method, which lead to the difficulty of localizing the frequency parameters of the spectrum over time [18,19].…”

Section: Related Workmentioning

confidence: 99%

“…After that, the components of the filtered matrix W m,k are used in the procedure of inverse wavelet transform to restore the cleared image. Expression ( 17) is used for a monochrome image, and expressions (18,19) are used for a multicolor image.…”

Section: Development Of the Mathematical Apparatusmentioning

confidence: 99%

“…Based on the requirements formed in [20,23,25], which ensure the efficiency of wavelet transforms, the expediency of using dyad discrete wavelet transform is determined, which reduces the computational complexity of the procedure for calculating wavelet coefficients by reducing the number of copies of the basic wavelet. The use of dyad discrete wavelet transform leads to the modification of expressions (13,14,(16)(17)(18)(19):…”

Section: Development Of the Mathematical Apparatusmentioning

confidence: 99%

“…9. Using the obtained values of the wavelet coefficients, with the help of expressions (17)(18)(19)(23)(24)(25) implement the inverse wavelet transform, which produces noiseless image.…”

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

Self Cite

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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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