Investigating the impact of motion visual synchrony on self face recognition using real time morphing
S Kasahara, N Kumasaki, K Shimizu - Scientific Reports, 2024 - nature.com
Face recognition is a crucial aspect of self-image and social interactions. Previous studies
have focused on static images to explore the boundary of self-face recognition. Our …
have focused on static images to explore the boundary of self-face recognition. Our …
Morphing Identity: Exploring Self-Other Identity Continuum through Interpersonal Facial Morphing Experience
We explored continuous changes in self-other identity by designing an interpersonal facial
morphing experience where the facial images of two users are blended and then swapped …
morphing experience where the facial images of two users are blended and then swapped …
Investigating effects of facial self-similarity levels on the impression of virtual agents in serious/non-serious contexts
Recent technological advances have enabled the use of AI agents to assist with human
tasks and augment human cognitive abilities in a variety of contexts, including decision …
tasks and augment human cognitive abilities in a variety of contexts, including decision …
Exploring the Lands Between: A Method for Finding Differences between AI-Decisions and Human Ratings through Generated Samples
Many important decisions in our everyday lives, such as authentication via biometric models,
are made by Artificial Intelligence (AI) systems. These can be in poor alignment with human …
are made by Artificial Intelligence (AI) systems. These can be in poor alignment with human …
The Effect of Latent Space Vector on Generating Animal Faces in Deep Convolutional GAN: An Analysis
İ Ataş - Dicle Üniversitesi Mühendislik Fakültesi Mühendislik … - dergipark.org.tr
Researchers are showing great interest in Generative Adversarial Networks (GANs), which
use deep learning techniques to mimic the content of datasets and are particularly adept at …
use deep learning techniques to mimic the content of datasets and are particularly adept at …