Technologies related to artificial intelligence (AI) have a strong impact on the changes of
research and creative practices in visual arts. The growing number of research initiatives …

In this article, we perform an exhaustive analysis of the use of Artificial Neural Networks and
Deep Learning in the Visual Arts. We begin by introducing changes in Artificial Intelligence …

We address the challenge of sentiment analysis from visual content. In contrast to existing
methods which infer sentiment or emotion directly from visual low-level features, we propose …

Text-driven sentiment analysis has been widely studied in the past decade, on both random
and benchmark textual Twitter datasets. Few pertinent studies have also reported visual …

In empirical aesthetics, choosing stimuli, especially artworks, is a persistent challenge.
Artworks differ largely in terms of style, complexity, formal features, and valence, as well as …

Visual content analysis has always been important yet challenging. Thanks to the popularity
of social networks, images become an convenient carrier for information diffusion among …

In this paper, we propose a new deep network that learns multi-level deep representations
for image emotion classification (MldrNet). Image emotion can be recognized through image …

In this work, I propose a model of visual aesthetic experience that combines formalist and
contextual aspects of aesthetics. The model distinguishes between two modes of …

ABSTRACT A multidisciplinary research was carried out to reach an improved
understanding of the connection between the geometry of space and human emotions. The …

Image aesthetic assessment (IAA) has been attracting considerable attention in recent years
due to the explosive growth of digital photography in Internet and social networks. The IAA …