Wearable devices are a fast-growing technology with impact on personal healthcare for both
society and economy. Due to the widespread of sensors in pervasive and distributed …

Deep neural networks have been applied in many applications exhibiting extraordinary
abilities in the field of computer vision. However, complex network architectures challenge …

Abstract Deep Neural Networks (DNN) have achieved state-of-the-art results in a wide range
of tasks, with the best results obtained with large training sets and large models. In the past …

Stochastic rounding (SR) randomly maps a real number x to one of the two nearest values in
a finite precision number system. The probability of choosing either of these two numbers is …

Solving real world problems with embedded neural networks requires both training
algorithms that achieve high performance and compatible hardware that runs in real time …

Deep neural networks are the state-of-the-art methods for many real-world tasks, such as
computer vision, natural language processing and speech recognition. For all its popularity …

Convolutional neural networks (CNNs) have become the dominant neural network
architecture for solving many state-of-the-art (SOA) visual processing tasks. Even though …

An ongoing challenge in neuromorphic computing is to devise general and computationally
efficient models of inference and learning which are compatible with the spatial and …

In recent years, the fields of natural language processing (NLP) and information retrieval (IR)
have made tremendous progress thanks to deep learning models like Recurrent Neural …

In recent years the field of neuromorphic low-power systems gained significant momentum,
spurring brain-inspired hardware systems which operate on principles that are …