Science Daily April 16, 2018
Researchers at the U.S. Army Research Laboratory used advanced domain adaptation techniques based on deep neural networks to overcome the challenge of cross-spectrum, or heterogeneous, face recognition to process thermal image of a person’s face captured in low-light or nighttime conditions. The fundamental approach is composed of two key parts: a non-linear regression model that maps a given thermal image into a corresponding visible latent representation and an optimization problem that projects the latent projection back into the image space. In face verification experiments using a common open source deep neural network architecture, their approach achieved better verification performance than a generative adversarial network-based approach… read more.