The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …

Recent years have witnessed an exponential increase in the use of mobile and embedded
devices. With the great success of deep learning in many fields, there is an emerging trend …

Convolutional neural networks, are one of the most representative deep learning models.
CNNs were extensively used in many aspects of medical image analysis, allowing for great …

Distributed denial of service (DDoS) is a special form of denial of service attack. In this
paper, a DDoS detection model and defense system based on deep learning in Software …

Abstract The security of Deep Neural Networks (DNNs) is of great importance due to their
employment in various safety-critical applications. DNNs are shown to be vulnerable against …

Currently, a large number of industrial data, usually referred to big data, are collected from
Internet of Things (IoT). Big data are typically heterogeneous, ie, each object in big datasets …

Over the past decade, deep learning models have exhibited considerable advancements,
reaching or even exceeding human-level performance in a range of visual perception tasks …

Energy saving is a critical and challenging issue for real-time systems in embedded devices
because of their limited energy supply. To reduce the energy consumption, a hybrid dynamic …

Recently, due to the increasing popularity of enjoying various multimedia services on mobile
devices (eg, smartphones, ipads, and electronic tablets), the generated mobile data traffic …

There has been an increased interest in multimodal language processing including
multimodal dialog, question answering, sentiment analysis, and speech recognition …