Visualization and edge computing for deep learning

Abstract

Our research looked into two aspects of deep learning. The first was visualization, for improving the understanding of how networks are able to make sense of complex input data. The second was deployment of Deep Learning networks on low-cost embedded computing devices that can provide data processing right at the source of data collected in a machine room.