Due to increasing amounts of data and compute resources, the deep learning achieves
many successes in various domains. Recently, researchers and engineers make effort to …

Due to increasing amounts of data and compute resources, deep learning achieves many
successes in various domains. The application of deep learning on the mobile and …

Deep learning (DL) has demonstrated great performance in various applications on
powerful computers and servers. Recently, with the advancement of more powerful mobile …

Recent years have witnessed an exponential increase in the use of mobile and embedded
devices. With the great success of deep learning in many fields, there is an emerging trend …

This paper presents the first industry-standard open-source machine learning (ML)
benchmark to allow performance and accuracy evaluation of mobile devices with different AI …

Although running deep-learning (DL) algorithms is challenging due to resource constraints
on mobile and wearable devices, they provide performance improvements compared to …

Detecting and reacting to user behavior and ambient context are core elements of many
emerging mobile sensing and Internet-of-Things (IoT) applications. However, extracting …

Deep neural networks (DNNs) have unleashed a new wave of applications on mobile
devices, such as various intelligent personal assistants. Most of these applications rely on …

Learn how to deploy effective deep learning solutions on cross-platform applications built
using TensorFlow Lite, ML Kit, and Flutter Key FeaturesWork through projects covering …

EdgeAI (Edge computing based Artificial Intelligence) has been most actively researched for
the last few years to handle variety of massively distributed AI applications to meet up the …