While high accuracy is of paramount importance for deep learning (DL) inference, serving
inference requests on time is equally critical but has not been carefully studied especially …

Machine learning inference applications have proliferated through diverse domains such as
healthcare, security, and analytics. Recent work has proposed inference serving systems for …

Deploying deep convolutional neural network (CNN) models on ubiquitous Internet of
Things (IoT) devices has attracted much attention from industry and academia since it …

An adaptive video object detection system selects different execution paths at runtime,
based on video content and available resources, so as to maximize accuracy under a target …

Machine learning (ML) is an important part of modern data science applications. Data
scientists today have to manage the end-to-end ML life cycle that includes both model …

Unstructured data (eg, video or text) is now commonly queried by using computationally
expensive deep neural networks or human labelers to produce structured information, eg …

Page 1 Advances in COMPUTERS Volume 127 Edge/Fog Computing Paradigm: The
Concept, Platforms and Applications Edited by PETHURU RAJ CHELLLAH, KAVITA SAINI …

Augmented reality (AR) underpins many emerging mobile applications, but it increasingly
requires more computation power for better machine understanding and user experience …

We believe that most future video uploaded over the network will be consumed by machines
for sensing tasks such as automated surveillance and mapping rather than for human …

Camera networks are essential to constructing fast and accurate mapping between virtual
and physical space for digital twin. In this paper, with the aim of developing energy-efficient …