Autonomic computing investigates how systems can achieve (user) specified “control”
outcomes on their own, without the intervention of a human operator. Autonomic computing …

Convolutional neural networks (CNNs) are one of the main types of neural networks used for
image recognition and classification. CNNs have several uses, some of which are object …

Driven by the quality of experience (QoE) requirement of video streaming applications in the
smart city, smart education, immersive service, and connected vehicle scenarios, the …

In recent times, the machine learning (ML) community has recognized the deep learning
(DL) computing model as the Gold Standard. DL has gradually become the most widely …

Abstract Human Activity Recognition (HAR) involves the recognition of human activities
using sensor data. Most of the techniques for HAR involve hand-crafted features and hence …

Cloud computing has become integral lately due to the ever-expanding Internet-of-things
(IoT) network. It still is and continues to be the best practice for implementing complex …

Cloud services offer doctors and data scientists access to medical data from multiple
locations using different devices (laptops, desktops, tablets, smartphones, etc.). Therefore …

Digitalization in the architecture, engineering, and construction (AEC) industry has
highlighted the process of gathering and combining data from numerous sources. This …

The increasing demand for automation and instant solution leads the technological world
towards massive applications such as the Internet of drones, Autonomous Vehicles (AVs) …

The substantial advancements offered by the edge computing has indicated serious
evolutionary improvements for the internet of things (IoT) technology. The rigid design …