Les progrès récents des réseaux de neurones artificiels (plus connus sous le nom d'apprentissage profond) ont permis d'améliorer l’état de l’art dans plusieurs domaines de la vision par ordinateur. Dans cette thèse, nous étudions des techniques d'apprentissage profond dans le cadre de l’analyse du genre et de l’âge à partir du visage humain. En particulier, deux problèmes complémentaires sont considérés : (1) la prédiction du genre et de l’âge, et (2) la synthèse et l’édition du genre et de l’âge.D’abord, nous effectuons une étude détaillée qui permet d’établir une liste de principes pour la conception et l’apprentissage des réseaux de neurones convolutifs (CNNs) pour la classification du genre et l’estimation de l’âge. Ainsi, nous obtenons les CNNs les plus performants de l’état de l’art. De plus, ces modèles nous ont permis de remporter une compétition internationale sur l’estimation de l’âge apparent. Nos meilleurs CNNs obtiennent une précision moyenne de 98.7% pour la classification du genre et une erreur moyenne de 4.26 ans pour l’estimation de l’âge sur un corpus interne particulièrement difficile.Ensuite, afin d’adresser le problème de la synthèse et de l’édition d’images de visages, nous concevons un modèle nommé GA-cGAN : le premier réseau de neurones génératif adversaire (GAN) qui produit des visages synthétiques réalistes avec le genre et l’âge souhaités. Enfin, nous proposons une nouvelle méthode permettant d’employer GA-cGAN pour le changement du genre et de l’âge tout en préservant l’identité dans les images synthétiques. Cette méthode permet d'améliorer la précision d’un logiciel sur étagère de vérification faciale en présence d’écarts d’âges importants. / The recent progress in artificial neural networks (rebranded as deep learning) has significantly boosted the state-of-the-art in numerous domains of computer vision. In this PhD study, we explore how deep learning techniques can help in the analysis of gender and age from a human face. In particular, two complementary problem settings are considered: (1) gender/age prediction from given face images, and (2) synthesis and editing of human faces with the required gender/age attributes.Firstly, we conduct a comprehensive study which results in an empirical formulation of a set of principles for optimal design and training of gender recognition and age estimation Convolutional Neural Networks (CNNs). As a result, we obtain the state-of-the-art CNNs for gender/age prediction according to the three most popular benchmarks, and win an international competition on apparent age estimation. On a very challenging internal dataset, our best models reach 98.7% of gender classification accuracy and an average age estimation error of 4.26 years.In order to address the problem of synthesis and editing of human faces, we design and train GA-cGAN, the first Generative Adversarial Network (GAN) which can generate synthetic faces of high visual fidelity within required gender and age categories. Moreover, we propose a novel method which allows employing GA-cGAN for gender swapping and aging/rejuvenation without losing the original identity in synthetic faces. Finally, in order to show the practical interest of the designed face editing method, we apply it to improve the accuracy of an off-the-shelf face verification software in a cross-age evaluation scenario.

This phenomenological study examined the experiences of women in midlife. The primary purpose of the study was to develop and describe a model of health promotion that will facilitate self-care of women in midlife to support them in the attainment of wholeness. A theory-generative, qualitative, explorative, descriptive and contextual design was utilized to achieve the objectives of the study, namely to explore and describe women's experience of midlife transition; classify concepts of the model; describe the structure and process of a model for support of women during midlife transition, and develop guidelines for operationalization of the model. The study was undertaken in one of the northwest states of the United States of America. Purposive sampling of eight women included women between the ages of 40 and 55 years of age. Women who had undergone surgical menopause were excluded as the influence of prolonged hormone replacement therapy was seen as a bias. Data was collected by using an unstructured interview technique. Data was analyzed according to Tesch's protocol (in Cresswell, 1994:155). Guba's model (in Krefting 1991:215) was utilized to ensure the trustworthiness of the study. Ethical issues were considered throughout and these are reflected in chapter one of the thesis. The study identified two themes: (1) how the women experienced midlife and (2) how they managed it. The experiences of midlife were expressed in physical, psychosocial and spiritual changes while the management of the process was accomplished in two ways, namely self-care and the services of healthcare professionals. The researcher identified that health promotion was essential to facilitate the self-care practices of women in midlife. Essential and related attributes of health promotion were identified, analyzed and synthesized to define health promotion. The process of health promotion was then defined with a description of the structure and process of the model. Concepts identified were classified, defined and placed into relationship statements after which the model was described and evaluated. Guidelines to operationalize the model were then formulated to assist health professionals to support women in self-care for the attainment of wholeness. / Health Studies / D.Litt et Phil (Health Studies)

This phenomenological study examined the experiences of women in midlife. The primary purpose of the study was to develop and describe a model of health promotion that will facilitate self-care of women in midlife to support them in the attainment of wholeness. A theory-generative, qualitative, explorative, descriptive and contextual design was utilized to achieve the objectives of the study, namely to explore and describe women's experience of midlife transition; classify concepts of the model; describe the structure and process of a model for support of women during midlife transition, and develop guidelines for operationalization of the model. The study was undertaken in one of the northwest states of the United States of America. Purposive sampling of eight women included women between the ages of 40 and 55 years of age. Women who had undergone surgical menopause were excluded as the influence of prolonged hormone replacement therapy was seen as a bias. Data was collected by using an unstructured interview technique. Data was analyzed according to Tesch's protocol (in Cresswell, 1994:155). Guba's model (in Krefting 1991:215) was utilized to ensure the trustworthiness of the study. Ethical issues were considered throughout and these are reflected in chapter one of the thesis. The study identified two themes: (1) how the women experienced midlife and (2) how they managed it. The experiences of midlife were expressed in physical, psychosocial and spiritual changes while the management of the process was accomplished in two ways, namely self-care and the services of healthcare professionals. The researcher identified that health promotion was essential to facilitate the self-care practices of women in midlife. Essential and related attributes of health promotion were identified, analyzed and synthesized to define health promotion. The process of health promotion was then defined with a description of the structure and process of the model. Concepts identified were classified, defined and placed into relationship statements after which the model was described and evaluated. Guidelines to operationalize the model were then formulated to assist health professionals to support women in self-care for the attainment of wholeness. / Health Studies / D.Litt et Phil (Health Studies)