5 research outputs found
Towards Automation and Human Assessment of Objective Skin Quantification
The goal of this study is to provide an objective criterion for computerised
skin quality assessment. Humans have been impacted by a variety of face
features. Utilising eye-tracking technology assists to get a better understanding
of human visual behaviour, this research examined the influence of face
characteristics on the quantification of skin evaluation and age estimation.
The results revealed that when facial features are apparent, individuals do
well in age estimation. Also, this research attempts to examine the performance
and perception of machine learning algorithms for various skin attributes.
Comparison of the traditional machine learning technique to deep
learning approaches. Support Vector Machine (SVM) and Convolutional Neural
Networks (CNNs) were used to evaluate classification algorithms, with
CNNs outperforming SVM. The primary difficulty in training deep learning
algorithms is the need of large-scale dataset. This thesis proposed two
high-resolution face datasets to address the requirement of face images for
research community to study face and skin quality. Additionally, the study
of machine-generated skin patches using Generative Adversarial Networks
(GANs) is conducted. Dermatologists confirmed the machine-generated images
by evaluating the fake and real images. Only 38% accurately predicted
the real from fake correctly. Lastly, the performance of human perception and
machine algorithm is compared using the heat-map from the eye-tracking experiment
and the machine learning prediction on age estimation. The finding
indicates that both humans and machines predict in a similar manner
Human History and Digital Future
Korrigierter Nachdruck. Im Kapitel "Wallace/Moullou: Viability of Production and Implementation of Retrospective Photogrammetry in Archaeology" wurden die Acknowledgemens enfternt.The Proceedings of the 46th Annual Conference on Computer Applications and Quantitative Methods in Archaeology, held between March 19th and 23th, 2018 at the University of Tübingen, Germany, discuss the current questions concerning digital recording, computer analysis, graphic and 3D visualization, data management and communication in the field of archaeology. Through a selection of diverse case studies from all over the world, the proceedings give an overview on new technical approaches and best practice from various archaeological and computer-science disciplines