Face recognition has made extraordinary progress owing to the advancement of deep
convolutional neural networks (CNNs). The central task of face recognition, including face …

Imprinting vision as memory is a core attribute of human cognitive learning. Fundamental to
artificial intelligence systems are bioinspired neuromorphic vision components for the visible …

Flexible neuromorphic electronics that emulate biological neuronal systems constitute a
promising candidate for next‐generation wearable computing, soft robotics, and …

Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …

Past research on facial expressions have used relatively limited datasets, which makes it
unclear whether current methods can be employed in real world. In this paper, we present a …

The fundamental mathematical tools needed to understand machine learning include linear
algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability …

Machine learning is enabling a myriad innovations, including new algorithms for cancer
diagnosis and self-driving cars. The broad use of machine learning makes it important to …

Conventional hardware platforms consume huge amount of energy for cognitive learning
due to the data movement between the processor and the off-chip memory. Brain-inspired …