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

… Further, shallow learning schemes are used for trainingbased color constancy, … Deep Neural
Networks (DNNs) to obtain accurate light source estimation. We reformulate color constancy …

… Color constancy refers to our capacity to see consistent colors under different illuminations.
… Here, we pursue an approach with deep neural networks that tries to assign reflectances to …

… Color constancy is our ability to perceive constant colors across varying illuminations. Here,
we trained deep neural networks to be color constant … Inputs to the networks consisted of two-…

… In this work we describe a Convolutional Neural Network (… color constancy, using a CNN
to learn discriminant features for the illuminant estimation task. Recently, deep neural networks …

… trained the convolutional neural network to solve the problem by casting the color constancy
… We designed the deep learning architecture so that the output of the network can be directly …

… However, in this paper, a new convolutional neural network architecture is … convolutional
neural network. Additionally, the common problem of the lack of data in color constancy …

… In this paper, we introduce a simple convolutional neural network without pre-trained layers,
… proposed a simple color constancy neural network made up of 5 convolutional layers. The …

… patch in the image to estimate the illuminant color. e spatial information could help more, if
… the image colors. In this work, we study the e ect of feeding a convolutional neural network a …

… the era of deep learning and convolutional neural networks, … framework for color constancy:
the convolutional framework (… combining its simplicity with the power of deep learning. This …