… Color constancy is the ability of the human visual system to perceive colors unchanged …
Additionally, we discuss the design of a new loss function oriented specifically to this …

… the assumption and coping with temporal color constancy under the varying illumination …
Effect on Loss Function – We test the effect of loss functions: the angular loss function vs. …

… loss function describes the actual loss for perception problems better than either the minus
delta loss function or the squared-error loss function. … loss for the local mass loss function as …

… In this work we focus on computation color constancy, using a CNN to learn discriminant
features for the illuminant estimation task. Recently, deep neural networks have …

… the color constancy task. In the second approach, we introduce composite objective function
… For this purpose, we modify the loss function of the autoencoder in the following manner: …

… in solving the color constancy problem. Secondly, we … color constancy using ML techniques.
The significance of this work provides a potential scope for some of the color constancy …

… To achieve these, we introduce a multiply-accumulate loss function for cascading convolutional
color constancy (e.g. FC 4 (Hu, Wang, and Lin 2017) in the experiments) to cope with …

… The softmax loss function is used for training. The aim of the first training step is to obtain a
pretrained feature model representing general images. Since the ImageNet dataset contains …

… Contemporary approaches frame the color constancy … framework that naturally handles color
constancy ambiguity via a multi… with the commonly used angular error loss function, where c …

… losses and test-set error rates than using only SGD, but more quickly than only using batch
L-BFGS. Though our loss function is … convex approximations to our loss function. Our problem …