The past decade has witnessed the great success of deep neural networks in various
domains. However, deep neural networks are very resource-intensive in terms of energy …

Guided by brain-like 'spiking'computational frameworks, neuromorphic computing—brain-
inspired computing for machine intelligence—promises to realize artificial intelligence while …

Neuromorphic Computing, a concept pioneered in the late 1980s, is receiving a lot of
attention lately due to its promise of reducing the computational energy, latency, as well as …

In recent years, deep learning has revolutionized the field of machine learning, for computer
vision in particular. In this approach, a deep (multilayer) artificial neural network (ANN) is …

Artificial neural networks have been used as a powerful processing tool in various areas
such as pattern recognition, control, robotics, and bioinformatics. Their wide applicability has …

The field of Deep Learning (DL) has seen a remarkable series of developments with
increasingly accurate and robust algorithms. However, the increase in performance has …

The primate visual system has inspired the development of deep artificial neural networks,
which have revolutionized the computer vision domain. Yet these networks are much less …

Reinforcement learning (RL) has recently regained popularity with major achievements such
as beating the European game of Go champion. Here, for the first time, we show that RL can …

Most of the image-text retrieval methods carry out accurate results using fine-grained
features for feature alignment. However, extracting the robustness features while …

Learning of hierarchical features with spiking neurons has mostly been investigated in the
database framework of standard deep learning systems. However, the properties of …