Researchers in the UK have developed a machine learning biometric system capable of identifying individuals from the shape of their hands. The intent of the work is to aide in identifying offenders, particularly in cases of sexual offenders that have recorded their crimes, where hand information is often the only biometric signal available. The paper, entitled Hand-based Person Identification Using Global and Part-aware Deep Feature Representation Learning, and proposes a new ML framework called Global and Part-Aware Network (GPA-Net). In GPA-Net, two distinct 3D tensors (global and local) are obtained by passing the source image through stacked convolutional layers on the ResNet50 backbone network. Each of the analytical avenues will make an identity prediction.