Gender recognition from unconstrained selfie images: a convolutional neural network approach

<p>Human gender recognition is an essential demographic tool. This is reflected in forensic science, surveillance systems and targeted marketing applications. This research was always driven using standard face images and hand-crafted features. Such way has achieved good results, however, the reliability of the facial images had a great effect on the robustness of extracted features, where any small change in the query facial image could change the results. Nevertheless, the performance of current techniques in unconstrained environments is still inefficient, especially when contrasted against recent breakthroughs in different computer vision research. This paper introduces a novel technique for human gender recognition from non-standard selfie images using deep learning approaches. Selfie photos are uncontrolled partial or full-frontal body images that are usually taken by people themselves in real-life environment. As far as we know this is the first paper of its kind to identify gender from selfie photos, using deep learning approach. The experimental results on the selfie dataset emphasizes the proposed technique effectiveness in recognizing gender from such images with 89% accuracy. The performance is further consolidated by testing on numerous benchmark datasets that are widely used in the field, namely: Adience, LFW, FERET, NIVE, Caltech WebFaces and<br />CAS-PEAL-R1.</p>

Two components of body-image disturbance are differentially associated with distinct eating disorder characteristics in healthy young women

Body-image disturbance comprises two components. The first is perceptual in nature, and is measured by a discrepancy between one’s actual body and perceived self-image (“perceived–actual discrepancy”). The other component is affective, and is measured by a discrepancy between one’s perceived self-image and ideal body image (“perceived–ideal discrepancy”). The present study evaluated the relationships between body-image disturbance and characteristics of eating disorders such as symptoms and related personality traits. In a psychophysiological experiment, female university students (mean ± SD age = 21.0 ± 1.38 years) were presented with silhouette images of their own bodies that were distorted in terms of width. The participants were asked whether each silhouette image was more overweight than their actual or ideal body images. Eating-disorder characteristics were assessed using six factors from the Japanese version of the Eating Disorder Inventory 2 (EDI2). We found that perceived–actual discrepancies correlated with negative self-evaluation (i.e., factor 3 of the EDI2), whereas perceived–ideal discrepancies correlated with dissatisfaction with one’s own body (i.e., factor 2 of EDI2). These results imply that distinct psychological mechanisms underlie the two components of body-image disturbance.

Classification of Brain Tumors Using Hybridized Convolutional Neural Network in Brain MRI images

In this research article, we have proposed a novel technique to operate on the Magnetic Resonance Imaging (MRI) data images which can be classified as image classification, segmentation and image denoising. With the efficient utilization of MRI images the medical experts are able to identify the medical disorders such as tumors which are correspondent to the brain. The prime agenda of the study is to organize brain into healthy and brain with tumor in brain with the test MRI data as considered. The MRI based technique is an methodology to study brain tumor based information for the better detailing of the internal body images when compared to other technique such as Computed Tomography (CT).Initially the MRI image is denoised using Anisotropic diffusion filter, then MRI image is segmented using Morphological operations, to classify the images for the disorder CNN based hybrid technique is incorporated, which is associated with five different set of layers with the pairing of pooling and convolution layers for the comparatively improved performance than other existing technique. The considered data base for the designed model is a publicly available and tested KAGGLE database for the brain MRI images which has resulted in the accuracy of 88.1%.

Effects of Breast Cancer on Women's Psychological Health: A Review of Self-Compassion-Based Interventions in Body Image

Research on how breast cancer and its treatment affect women's psychological health is increasing day by day. There is information that the psychological health of women is affected not only in the treatment, but also during the period from cancer diagnosis to the beginning of cancer treatment. In recent years, pre-rehabilitation intervention, which is an up-to-date approach that recommends intervention in this process, comes to the fore. The problems women experience with their body images have an important place in the effects of breast cancer and its treatment on women's psychological health. Body image is defined as a conceptualized state of the emotions, thoughts and behaviors that a person feels about their physical characteristics. In recent years, interventions aimed at reducing body image problems in women with breast cancer have been increasing. Self-compassion is defined as an individual's approach to their flaws with a sincere, caring and warm attitude. The emphasis on the role of self-compassion in reducing the problems that women with breast cancer experience with body images is increasing day by day. Based on this information, in this study, the literature on the problems faced by women with breast cancer with their body image and the role of self-compassion in reducing these problems is reviewed and discussed within the scope of pre-rehabilitation intervention. Keywords: Self-compassion, breast cancer survivors, interventions for self-compassion, body image

Impact of Face Masks on Female Body Perception is Modulated by Facial Expressions

People routinely wear face masks during the pandemic, but little is known about their impact on body perception. In this online study, we presented female body images of Caucasian avatars in common dress sizes displaying happy, angry, and neutral facial expressions with and without face masks, and asked women to rate the perceived body attractiveness and body size. In comparison with mask-off condition, mask-on decreased body attractiveness ratings for happy avatars but did not affect ratings for neutral avatars irrespective of avatar dress sizes. For avatars displaying angry expressions, mask-on increased body attractiveness ratings for slimmer avatars but did not affect ratings for larger avatars. On the other hand, body size estimation was not systematically affected by face masks and facial expressions. It appears that face masks mainly show an expression-dependent influence on body attractiveness judgement, possibly through suppressing the perceived facial expressions.

The Effects of Media and Peers on Negative Body Images of Chinese College Students: Multiple Mediating Effects of Appearance Comparison and Internalization of the Thin-Ideal

Background Negative body image is a common psychological phenomenon among Chinese college students, which should arouse our attention. Peers and media are important factors that influence personal negative body image. This study explores the mechanism of media and peers on the negative body image of Chinese college students. Methods 461 college students (173 identifying as male, 234 identifying as female) were investigated by using the Revised Social and Cultural Attitude Questionnaire of Appearance, Appearance Comparison Scale, Peer Impact Scale and Negative Body Image Scale. Results The results are as follows: (1) Correlation analysis shows that except media attention is not significantly correlated with negative body images, all other variables are significantly positively correlated; (2) Path analysis shows that the direct effect of media attention on negative body image is not significant, while the direct effect of peer impact is significant, and both of them have indirect effects through the mediate role of appearance comparison and internalization of the thin-ideal. Additionally, appearance comparison and internalization of the thin-ideal act as a chain mediation between negative body image and media attention, peer impact. Conclusions The research shows just paying attention to the information of the perfect body in the media will not produce negative body image, but paying attention to the media and peer talks about the body may cause college students to compare appearances and internalize the standards for a good shape, leading to their negative evaluation of themselves.

A Critical Discourse Analysis for Advertisements in Instagram: Calvin Klein, Tommy Hilfiger and H&M

Online Advertising has a significant influence in this modern century; because of this, famous companies effectively use online advertisements to introduce their products. Such as Calvin Klein, H&M, and Tommy Hilfiger are some famous brand companies that use advertisements on social media for their marketing strategies. Those companies have influential followers on Instagram, and they reach many people around the world. Thus, they use online media to sell their products and deliver their cultural values to reach the target audiences. Namely, famous brand companies want to be part of the social changes. Because of this, they use visual and verbal discursive strategies for their advertisements to influence and change socio-cultural values and stereotypes of people. In other words, advertisers use discursive language to persuade people to buy beliefs, values, and ideas besides commercial products. The visual and verbal language in online advertisements reveals the hidden meanings of stereotypes: body image, racism, and LGBT rights. Therefore, the qualitative analysis method uses to analyze the brands' advertisements. As a qualitative method, the writer applies the Critical Discourse Analysis to reveal the hidden meanings of Tommy Hilfiger, H&M, Calvin Klein’s Instagram Advertisement Photos. The analysis and interpretation reveal that advertisers use different people to show that those companies think about everyone and want to reach everyone. The body type is not essential, and consumers can find different sizes of clothes. In addition, advertisers promote different body images to shape society's ideas to purchase their products and show like celebrities, who are confident, happy with their color, body size, sexual orientation, and ethnic minorities. Even visual and verbal languages show that differences are beautiful and make you forget/remove your boundaries to be free.

The Ideal Body: A Social Construct? Reflections on Body Pressure and Body Ideal Among Students in Upper Secondary School

Several studies show that young people today are negatively impacted by body image ideals in social media. We studies young people's reflections on body image and body pressure. More precisely: How does a selected group of third-year upper secondary school students understand their body images and body pressures through social media? Eight third-year students, four of each gender, were interviewed from two upper secondary schools in a medium-sized city in Norway. An interesting find was that body pressure was not experienced solely as one-sided pressure exerted externally by media sources, but that they also personally influenced others through their own active use of social media channels like Facebook and Instagram. They reported having experienced body pressure in their own lives and in their immediate environment, and that both genders are affected. The study builds on sociocultural body theory based on Foucault's ideas and work, but also uses more recent media theory for the analysis and discussion. A BOPS model developed by the researchers was used for the operational parameters that is centered around the concepts of panopticon, synopticon and omniopticon.

Skin Lesion Detection Algorithms in Whole Body Images

Melanoma is one of the most lethal and rapidly growing cancers, causing many deaths each year. This cancer can be treated effectively if it is detected quickly. For this reason, many algorithms and systems have been developed to support automatic or semiautomatic detection of neoplastic skin lesions based on the analysis of optical images of individual moles. Recently, full-body systems have gained attention because they enable the analysis of the patient’s entire body based on a set of photos. This paper presents a prototype of such a system, focusing mainly on assessing the effectiveness of algorithms developed for the detection and segmentation of lesions. Three detection algorithms (and their fusion) were analyzed, one implementing deep learning methods and two classic approaches, using local brightness distribution and a correlation method. For fusion of algorithms, detection sensitivity = 0.95 and precision = 0.94 were obtained. Moreover, the values of the selected geometric parameters of segmented lesions were calculated and compared for all algorithms. The obtained results showed a high accuracy of the evaluated parameters (error of area estimation <10%), especially for lesions with dimensions greater than 3 mm, which are the most suspected of being neoplastic lesions.

Computational Journalism Analysis on Young Adults' Body Images and Attitudes Toward Plastic Surgery

Computational journalism, especially social media analysis, is a very popular field in computational science. This study was conducted to explore and analyze the impact of the intensity of the exposure to social media on young Thai adults' body images and attitudes toward plastic surgery. The purposive sampling method was used for choosing 250 young Thai men and women aged 21 to 40 who used Facebook and/or Instagram on a regular basis. Online survey questionnaires were posted on Facebook for one month to achieve the results. It was found that young Thai adults frequently and heavily used both social media. Having appearance pressure from and repeated social comparison with idealistic media images, a considerable number of participants displayed more negative self-perceptions and engaged in appearance-changing strategies through increased appearance investment. The results showed that the more these young adults were exposed to social media, the more they were likely to develop a negative body image of themselves, which later caused their attitude toward plastic surgery to be positive.