Abstract: Systems, methods, and non-transitory computer-readable media embed a trained neural network within a digital image. For instance, in one or more embodiments, the systems identify out-of-gamut pixel values of a digital image in a first gamut, where the digital image is converted to the first gamut from a second gamut. Furthermore, the systems determine target pixel values of a target version of the digital image in the first gamut that correspond to the out-of-gamut pixel values. The systems train a neural network to predict the target pixel values in the first gamut based on the out-of-gamut pixel values. The systems embed the neural network within the digital image in the second gamut to allow for extraction of the embedded neural network from the digital image to restore the digital image to a larger gamut digital image.

Abstract: Various embodiments of a voltage detection device and of related safety systems are provided. In various embodiments, the voltage detection device is configured to couple to safety headwear, such as via the one or more housing(s) of the voltage detection device coupling directly to the safety headwear or the voltage detection device coupling to an adaptor mounted to the hard hat.

Abstract: A method of making silethynyl-siloxane copolymers having R.sub.2 SiC.tbd.C units and R.sub.2 SiO units wherein each R denotes H or a C.sub.1-16 hydrocarbon or substituted hydrocarbon group, comprises ring-opening copolymerization in the presence of a catalytic amount of a lithium compound, of cyclic siloxanes and cyclic silethynyl polymers. Novel silethynyl-siloxane copolymers of the formula ##STR1## are also disclosed wherein R' denotes --C.tbd.CH or R and a and b are at least 1.