Forging Emotions: a deep learning experiment on emotions and art

Affective computing is an interdisciplinary field that studies computational methods relate to or influence emotion. These have been applied interactive media artworks, but they focused on affect detection rather than generation. For generation, computationally creative need be explored recently driven by the use of Generative Adversarial Networks (GANs), a deep learning method. The experiment presented in this paper, Forging Emotions, explores visual emotion datasets and working processes GANs for is, generating images can convey trigger specified emotions. This concludes methodology used so far computer science researchers build image describing high-level concepts such as emotions insufficient proposes utilizing emotional networks associations according psychology research. Emotions also generate visually, merely corresponding basic findings, bright dark colours, does not seem adequate. Therefore, research efforts should aim understand structure trained compositional order produce genuinely novel compositions through subject matter generated images.