Extrapolating continuous color emotions through deep learning

To carry out our mathematical study, we have used the standard Decimal Code (R,G,B) to represent the 12 colours of [12], a depiction of which is in Figure 1. The relation between colours and human emotion has been studied for more than a century (e.g., see for instance [1-8]). Even longer ago, colours were commonly associated to emotions in a universal manner that allowed populations to understand quickly the given emotions. Figure 1: A depiction of the 12 colors used in [12]. For example, for centuries in many cultures it has been said that someone "had the blues" [29] or "is feeling In the last decades colours have also been studied in blue" when being down or sad. As explained in [9], the terms of emotional reactions to color hue, saturation, and phrase "feeling blue" comes from deepwater sailing ships: brightness (e.g., [14, 15]). Here, we shall put the two If a ship lost the captain or any of the officers during its approaches together to consider a novel path, where we voyage, then blue flags would be shown, and a blue band let the colour association within our neural network take would be painted along the entire hull when returning to a continuum of colours, hence considering a continuous home port. RGB analysis [30], depicted in Figure 2. Inspired by [10, 11] we consider their data base [12] to analize the correlation between colours and emotions via a deep learning approach. Whilst machine learning techniques have been used before in this direction (e.g.