… color constancy can be learned by a standard neural network. Of course, the disadvantage
of the neural network … there is no way to know exactly what it is that the network learned. The …

… Abstract-This paper presents a neural network approach to the problem of color constancy.
Various … color constancy abilities and qualitatively mimics aspects of human color perception. …

… successfully trained neural net calculates color differences … to the neural net, we conclude
that to satisfy the color constancy … the background color and the other to estimate the color …

… Neural networks (NNs) and support vector regression (SVR) in particular, have been shown
to outperform many traditional color constancy algorithms. However, neither neural networks …

… be used to fool deep neural networks (DNNs) into pro… color constancy, which makes up
the white-balance (WB) routine on digital cameras. We focus on computational color constancy …

… Natural Illuminants: Because of the importance for practical applications and for evolutionary
significance, we begin by looking at the color constancy abilities of the network under …

… can make use of color constancy processing as a pre… color constancy, using a CNN to learn
discriminant features for the illuminant estimation task. Recently, deep neural networks have …

… In this paper, we present a review of established color constancy … neural networks achieved
better color constancy than color by correlation [13]. Ebner [17] proposed a neural network …

… and human vision color constancy. The method proposed in this paper relates to the computer
vision color constancy. The most important part of the computer vision color constancy is …

… Color constancy is our ability to perceive constant colors across varying illuminations. Here,
we trained deep neural networks to be color constant and evaluated their performance with …