The increasing adoption of smart systems in our daily life has led to the development of new
applications with varying performance and energy constraints, and suitable computing …

Crowdsourcing enables a paradigm to conduct the manual annotation and the analytics by
those recruited workers, with their rewards relevant to the quality of the results. Existing …

The growth of video volumes and increased DNN capabilities have led to a growing desire
for video analytics, which demands intensive computation resources. Traditional resource …

Abstract Deep Neural Network (DNN) based video analytics empowers many computer
vision-based applications to achieve high recognition accuracy. To reduce inference delay …

With the advancements in Machine Learning (ML) and edge computing, increasing efforts
have been devoted to edge video analytics. However, most of the existing works fail to …

Deep Neural Network (DNN)-based video analytics significantly improves recognition
accuracy in computer vision applications. Deploying DNN models at edge nodes, closer to …

Deep learning-based video analytics is computation-intensive. Manufacturers such as
Nvidia have launched many embedded deep learning accelerators and are rapidly gaining …

Edge-based live video analytics are a promising approach to reduce bandwidth overheads
caused by the transmission of raw video streams to the cloud. However, the limited …

To harness the potential of edge resources, two-tier client-cloud applications require
transformation into three-tier client-edge-cloud applications. Such transformations are hard …

The article introduces a novel strategy for efficiently mitigating COVID-19 distribution at the
local level due to contact with any surfaces. Our project aims to be a critical safety shield for …