This study is the first to provide an integrated view on the body of knowledge of artificial
intelligence (AI) published in the marketing, consumer research, and psychology literature …

Ubiquitous sensors and smart devices from factories and communities are generating
massive amounts of data, and ever-increasing computing power is driving the core of …

Deep learning is currently widely used in a variety of applications, including computer vision
and natural language processing. End devices, such as smartphones and Internet-of-Things …

With the breakthroughs in deep learning, the recent years have witnessed a booming of
artificial intelligence (AI) applications and services, spanning from personal assistant to …

Most existing Augmented Reality (AR) and Mixed Reality (MR) systems are able to
understand the 3D geometry of the surroundings but lack the ability to detect and classify …

Despite existing work in machine learning inference serving, ease-of-use and cost efficiency
remain challenges at large scales. Developers must manually search through thousands of …

Abstract In the Internet of Things enabled intelligent transportation systems, a huge amount
of vehicle video data has been generated and real-time and accurate video analysis are …

Video streaming is crucial for AI applications that gather videos from sources to servers for
inference by deep neural nets (DNNs). Unlike traditional video streaming that optimizes …

To cope with the high resource (network and compute) demands of real-time video analytics
pipelines, recent systems have relied on frame filtering. However, filtering has typically been …

Organizations deploy a hierarchy of clusters-cameras, private clusters, public clouds-for
analyzing live video feeds from their cameras. Video analytics queries have many …