With the increasing amount of data produced and collected, use artificial intelligence technologies has become inevitable. By using deep learning techniques from these technologies, high performance can be achieved in tasks such as classification face analysis fields image processing computer vision. In this study, Convolutional Neural Networks (CNN), one algorithms, was used. The model created...

Face land-marking, defined as the detection and positioning of distinctive characteristics, is a crucial goal shared by various organizations, ranging from biometric recognition to mental state comprehension. Despite its apparent simplicity, this problem has been extensively investigated because inherent face variability variety confusing variables such posture, voice, illumination, occlusions....

Recent research has revealed that learning behavior is associated with academic achievement at the college level, but the impact of specific learning strategies on academic success as well as gender differences therein are still not clear. Therefore, the aim of this study was to investigate gender differences in the incremental contribution of learning strategies over general cognitive ability ...

OBJECTIVE Develop a gender specific database of trunk muscle cross-sectional areas across multiple levels of the thoracic and lumbar spine and develop prediction equations for the physiological cross-sectional area as a function of gender and anthropometry. DESIGN This study quantified trunk muscle cross-sectional areas of male and female spine loading muscles. BACKGROUND There is a lack of...

We present three competing predictions of the organizational gender diversityperformance relationship: a positive linear prediction, a negative linear prediction, and an inverted U-shaped curvilinear prediction. The paper also proposes a moderating effect of industry type (services vs. manufacturing). The predictions were tested using archival quantitative data with a longitudinal design. The r...

In this paper we present a set of experiments and analyses on predicting the gender of Twitter users based on languageindependent features extracted either from the text or the metadata of users’ tweets. We perform our experiments on the TwiSty dataset containing manual gender annotations for users speaking six different languages. Our classification results show that, while the prediction mode...

Social media provides users a platform to publish messages and socialize with others, and microblogs have gained more users than ever in recent years. With such usage, user profiling is a popular task in computational linguistics and text mining. Different approaches have been used to predict users’ gender, age, and other information, but most of this work has been done on English and other Wes...

This paper is concerned in analyzing iris texture in order to determine “soft biometric”, attributes of a person, rather than identity. In particular, this paper is concerned with predicting the gender of a person based on analysis of features of the iris texture. Previous researchers have explored various approaches for predicting the gender of a person based on iris texture. We explore using ...