Convolutional neural networks (CNNs) have dominated the field of computer vision for nearly a decade. However, due to their limited receptive field, CNNs fail model global context. On other hand, transformers, an attention-based architecture, can context easily. Despite this, there are studies that investigate effectiveness transformers in crowd counting. In addition, majority existing crowd-co...

Parallel Distributed Processing (PDP) models have had a profound impact on the study of cognition. One domain in which they have been particularly influential is quasiregular learning, in which mastery requires both learning regularities that capture the majority of the structure in the input plus learning exceptions that violate the regularities. How PDP models learn quasiregularity is still n...