Abstract Recently, Deep Convolutional Neural Network (DCNN) has been recognized as the
most effective model for pattern recognition and classification tasks. With the fast growing
Internet of Things (IoTs) and wearable devices, it becomes attractive to implement DCNNs in
embedded and portable systems. However, novel computing paradigms are urgently
required to deploy DCNNs that have huge power consumptions and complex topologies in
systems with limited area and power supply. Recent works have demonstrated that …