Multiple hierarchical decision on neural network to predict human age and gender

Dileep, M. R.; Danti, Ajit

doi:10.1109/icetets.2016.7603026

Cited by 7 publications

(5 citation statements)

References 6 publications

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“…Термин «социальная сеть» обозначает сосредоточение социальных объектов, которые можно Vitaly R. Grigoriev, Dmitry O. Zhukov Models and methods for analyzing complex networks and social network structures Russian Technological Journal. 2023;11(2): [33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49] то сегодня электронные сети эту задачу несколько упростили. Это произошло за счет использования пассивных данных (таких как веб-страницы и данные почтовых хранилищ).…”

Section: социальные сети и их общие свойстваunclassified

“…Григорьев, Д.О. Жуков Модели и методы анализа сложных сетей и социальных сетевых структур Исследования в статьях [37][38][39][40][41] направлены на анализ профилей в социальных сетях с использованием гендерной классификации, которая решала проблему распознавания лиц с помощью нейронных сетей, алгоритмов, работающих с использованием смайликов-эмоджи в исходном тексте и определения возраста и пола по фотографии.…”

Section: анализ сетевых структур и прогнозирование динамики обществен...unclassified

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Models and methods for analyzing complex networks and social network structures

Perova

Grigoriev

Zhukov

2023

Rossijskij tehnologičeskij žurnal

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Objectives. The study aimed to investigate contemporary models, methods, and tools used for analyzing complex social network structures, both on the basis of ready-made solutions in the form of services and software, as well as proprietary applications developed using the Python programming language. Such studies make it possible not only to predict the dynamics of social processes (changes in social attitudes), but also to identify trends in socioeconomic development by monitoring users’ opinions on important economic and social issues, both at the level of individual territorial entities (for example, districts, settlements of small towns, etc.) and wider regions.Methods. Dynamic models and stochastic dynamics analysis methods, which take into account the possibility of self-organization and the presence of memory, are used along with user deanonymization methods and recommendation systems, as well as statistical methods for analyzing profiles in social networks. Numerical modeling methods for analyzing complex networks and processes occurring in them are considered and described in detail. Special attention is paid to data processing in complex network structures using the Python language and its various available libraries.Results. The specifics of the tasks to be solved in the study of complex network structures and their interdisciplinarity associated with the use of methods of system analysis are described in terms of the theory of complex networks, text analytics, and computational linguistics. In particular, the dynamic models of processes observed in complex social network systems, as well as the structural characteristics of such networks and their relationship with the observed dynamic processes including using the theory of constructing dynamic graphs are studied. The use of neural networks to predict the evolution of dynamic processes and structure of complex social systems is investigated. When creating models describing the observed processes, attention is focused on the use of computational linguistics methods to extract knowledge from text messages of users of social networks.Conclusions. Network analysis can be used to structure models of interaction between social units: people, collectives, organizations, etc. Compared with other methods, the network approach has the undeniable advantage of operating with data at different levels of research to ensure its continuity. Since communication in social networks almost entirely consists of text messages and various publications, almost all relevant studies use textual analysis methods in conjunction with machine learning and artificial intelligence technologies. Of these, convolutional neural networks demonstrated the best results. However, the use of support vector and decision tree methods should also be mentioned, since these contributed considerably to accuracy. In addition, statistical methods are used to compile data samples and analyze obtained results.

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Section: социальные сети и их общие свойстваunclassified

Section: анализ сетевых структур и прогнозирование динамики обществен...unclassified

Models and methods for analyzing complex networks and social network structures

Perova

Grigoriev

Zhukov

2023

Rossijskij tehnologičeskij žurnal

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“…Face provides perceptible information related to human trait. Among all approaches [20][21][22][23][24][25][26][27][28][29][30] face images are easily available evidences for the age estimation in human identification and much of work done on this feature. Social networking websites, shopping websites, matrimony websites, and criminal database images provides plenty of digital human facial images.…”

Section: ) Face Examinationmentioning

confidence: 99%

Features and Methods of Human Age Estimation: Opportunities and Challenges in Medical Image Processing

Patil¹

2021

TURCOMAT

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Age estimation of living species is an open and interesting problem due to its medico-legal importance and humans are no exception to this. Human body undergoes various physiological changes such as facial wrinkles, walking habits. Besides this, biological changes also help in human age estimation. Some of the changes are body skeleton and craniofacial growth. Various age estimation methods viz. manual, semi-automated and automated methods are available. Each of these methods has their merits and demerits. The popular manual and semi-automated age estimation methods are prone to human observation error and need sophisticated equipments. The advent of computational methods has opened new possibilities towards automation of the problem. Hence there is growing interest in fully automated methods. Through this paper, we have discussed different aspects of human age estimation and presented a brief review of various available methods.

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“…Early work on gender prediction attempted to predict gender based on the facial features, a person's face provides a lot of in-formation such as age, gender and identity. Michele, Liangliang and John [14] proposed a method to extract gender information from the pictures posted in social media feeds and achieved 88% mean accuracy; Dileep M R and Ajit Danti [9] proposed an effective method named Multiple Hierarchical decision based on Neural Networks to predict human age and gender from facial images. Fake biometric identifiers can be of the form where one person imitates as another, so Anusree Bhaskar [10] presented a software based multi-biometric system to classify real and fake face samples and gender classification.…”

Section: 3gender Predictionmentioning

confidence: 99%

“…The difficulty in classifying men and women in retail scenario raises an interesting research question: Can we inference users' gender automatically only based on their purchase behaviors and other known external factors? Although some recent studies suggest that gender attributes are predictable from different behavioral data, such as linguistics writing [5,6,7,8], facial images [9,10,11], social media [12,13,14] and mobile data [15] to our best knowledge, seldom practice has been conducted on purchase behaviors in retail scenario.…”

Section: Introductionmentioning

confidence: 99%

Gender Prediction of Consumers Using Offline Purchase Data

Ji¹

2018

Proceedings of the 2017 4th International Conference on Machinery, Materials and Computer (MACMC 2017)

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Demographic attributes such as gender of consumers provide important in-formation for marketing, personalization, and user behavior research. With the growing necessity for gender information in personalized intelligent systems, gender prediction of consumers has become an important research issue. This paper addresses the problem of predicting consumers' gender based on purchase data and some external factors, such as weather and name. According to the characteristics of offline data, we compared the performance of different algorithms and the contribution of different features to gender prediction was compared. From the experiments conducted on real-world datasets, we found the most important features and the best performing algorithms that influenced the gender prediction of offline purchase da-ta. This study provided suggestions for apparel offline markets to develop effective marketing strategies to reach their target market, for consumer educators and for educators in the retail merchandizing area to prepare their students for future careers.

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Multiple hierarchical decision on neural network to predict human age and gender

Cited by 7 publications

References 6 publications

Models and methods for analyzing complex networks and social network structures

Models and methods for analyzing complex networks and social network structures

Features and Methods of Human Age Estimation: Opportunities and Challenges in Medical Image Processing

Gender Prediction of Consumers Using Offline Purchase Data

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