سیویلیکا را در شبکه های اجتماعی دنبال نمایید.

Kinship Recognition based on Deep Scattering Wavelet Convolutional Neural Network on Wild Facial Image

Publish Year: 1403
Type: Journal paper
Language: English
View: 139

This Paper With 11 Page And PDF Format Ready To Download

این Paper در بخشهای موضوعی زیر دسته بندی شده است:

Export:

Link to this Paper:

Document National Code:

JR_MJEE-18-1_002

Index date: 28 April 2024

Kinship Recognition based on Deep Scattering Wavelet Convolutional Neural Network on Wild Facial Image abstract

Kingship verification is a process that two or more people has a family relation such as father and son or other family relation. Numerous studies have been presented to investigate the relationship between people. Kingship verification can be done based on image of face. Most of the methods presented on face images work well on face data sets recorded under controlled conditions. However, due to the complex nature of environments, rapidly and accurately examining human kinship in real-world unrestricted or wild-type scenarios is still a challenging research. In this paper, in order to overcome the aforementioned challenges, an efficient and new method is presented. In the proposed method, a method is used to launch the operation to create a map. The created feature map is stable against deformation, transition, scaling, direction and Dilation in wild images. Group-Face and TSKinFace databases are used for simulation. In order to evaluate the evaluation of the proposed method, average recall of 94.1, precision 94.6, accuracy 94.7, specificity 93.8, and finally F_Measure 95.0 were used. The superiority of the proposed method in all comparisons shows the effectiveness of the proposed method in diagnosing kinship.

Kinship Recognition based on Deep Scattering Wavelet Convolutional Neural Network on Wild Facial Image Keywords:

Kinship Recognition based on Deep Scattering Wavelet Convolutional Neural Network on Wild Facial Image authors

somayeh arab Najafabadi

Department of Computer Engineering, Arak Branch, Islamic Azad University, Arak, Iran

Sara Nazari

Department of Computer Engineering, Arak Branch, Islamic Azad University, Arak, Iran

Nafiseh Osati Eraghi

Department of Computer Engineering, Arak Branch, Islamic Azad University, Arak, Iran

مراجع و منابع این Paper:

لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :
F. Fuller, E. F. Fuchs, and K. J. Roesler, “Influence ...
H. Miller, “A note on reflector arrays, ” IEEE Trans. ...
J. Vidmar. (۱۹۹۲, Aug.). On the use of atmospheric plasmas ...
O. Young, “Synthetic structure of industrial plastics, ” in Plastics, ...
Jones. (۱۹۹۱, May ۱۰). Networks. (۲nd ed.) [Online]. Available: http://www.atm.comE. ...
L. Talleen. (۱۹۹۶, Apr.). The Intranet Architecture: Managing information in ...
Process Corp., Framingham, MA. Intranets: Internet technologies deployed behind the ...
Hwang, “Frequency domain system identification of helicopter rotor dynamics incorporating ...
IEEE Guide for Application of Power Apparatus Bushings, IEEE Standard ...
Brandli and M. Dick, “Alternating current fed power supply, ” ...
نمایش کامل مراجع