Recent advances in machine learning and deep learning have enabled many existing
applications in smart cities, autonomous systems, and wearable devices. These applications …

Video analytics with deep learning techniques has generated immense interest in academia
and industry, captivating minds with its transformative potential. Deep learning techniques …

Cloud computing and edge computing models are popularly applied in emerging
applications, such as smart homes, smart parks, and connected autonomous vehicles for …

Emerging Internet of Things (IoT) and mobile computing applications are expected to
support latency-sensitive deep neural network (DNN) workloads. To realize this vision, the …

With the booming development of Internet-of-Things (IoT) and communication technologies
such as 5G, our future world is envisioned as an interconnected entity where billions of …

Along the trend pushing computation from the network core to the edge where the most of
data are generated, edge computing has shown its potential in reducing response time …

Now we are entering the era of the Internet of Everything (IoE) and billions of sensors and
actuators are connected to the network. As one of the most sophisticated IoE applications …

An edge cloud is a highly distributed heterogeneous edge infrastructure that follows
principles of disaggregated, cloud-native, fully orchestrated, and provisioned architecture …

Emerging Internet of Things (IoT) and mobile computing applications are expected to
support latency-sensitive deep neural network (DNN) workloads. To realize this vision, the …

Deep learning with Deep Neural Networks (DNNs) can achieve much higher accuracy on
many computer vision tasks than classic machine learning algorithms. Because of the high …