Edge computing and artificial intelligence (AI), especially deep learning algorithms, are
gradually intersecting to build the novel system, namely edge intelligence. However, the …

Neural Architecture Search (NAS) methods have been growing in popularity. These
techniques have been fundamental to automate and speed up the time consuming and error …

Medical data widely exist in the hospital and personal life, usually across institutions and
regions. They have essential diagnostic value and therapeutic significance. The disclosure …

Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning
(DL) is already present in many applications ranging from computer vision for medicine to …

HardWare-aware Neural Architecture Search (HW-NAS) has recently gained tremendous
attention by automating the design of DNNs deployed in more resource-constrained daily …

Abstract Knowledge extraction through machine learning techniques has been successfully
applied in a large number of application domains. However, apart from the required …

Deep neural networks (DNN) are now dominating in the most challenging applications of
machine learning. As DNNs can have complex architectures with millions of trainable …

There is no doubt that making AI mainstream by bringing powerful, yet power hungry Deep
Neural Networks (DNNs) to resource-constrained devices would require an efficient co …

The security and privacy concerns along with the amount of data that is required to be
processed on regular basis has pushed processing to the edge of the computing systems …

Over the past few years, the computer vision domain has evolved and made a revolutionary
transition from human-engineered features to automated features to address challenging …